O. Fedorovich, Oleg Uruskiy, I. Chepkov, Mikhail Lukhanin, Yu. Pronchakov, K. Rybka, Yuliia Leshchenko
The multi-criteria task related to the simulation of transport logistics for the delivery of military cargo to the war zone in the conditions of delays and risks is stated and solved. The relevance of the study is related to the analysis of possible losses in the war zone (loss of armed forces, damage and destruction of military equipment, change in hostilities from offensive to defensive, etc.) due to the delayed supply of weapons and military equipment. The study simulates the logistics of transportation in the diverse transport networks to ensure timely delivery of military cargo in the conditions of possible delays and risks that affect the amount of damage in the war zone. Given the complex dynamics of military cargo delivery related to heterogeneity and transshipment in the transport network, the original agent simulation model has been created. This model makes it possible to study the supply process and allows to assess delays, risks and losses. A new algorithm to minimize the delivery time of military cargo, based on the distribution of request clones in a graph representing a heterogeneous transport network is presented. An algorithm to minimize supply risks in wartime that considers long logistics chains for transporting military cargo to the war zone is presented. We study the losses caused by the untimely arrival of various types of military equipment and weapons in the war zone, based on full factorial experiments and the assessments of military experts in the field of military logistics are conducted. Given the contradictions of the criteria of delays, risks and losses, the multi-criteria problem of compromise search optimization based on integer (Boolean) programming is stated and solved. The efficiency of the proposed approach is demonstrated by simulating military cargo supply to the war zone. Alternative supply routes, risks and losses due to delays in supply are analyzed. The choice of the compromise alternative of military cargo delivery route to the war zone is substantiated. The scientific novelty of the study is related to the development of methods and models based on agent simulation, experimental theory and integer optimization, that makes it possible to estimate the delays and losses in the supply of military cargo to the war zone in long logistics chains of diverse transport network. The results of the study can be used to build the optimal routes to supply military cargo in wartime.
{"title":"Моделювання транспортної логістики військових вантажів з урахуванням збитків, які виникають у зоні бойових дій через запізнення у постачанні","authors":"O. Fedorovich, Oleg Uruskiy, I. Chepkov, Mikhail Lukhanin, Yu. Pronchakov, K. Rybka, Yuliia Leshchenko","doi":"10.32620/reks.2022.2.05","DOIUrl":"https://doi.org/10.32620/reks.2022.2.05","url":null,"abstract":"The multi-criteria task related to the simulation of transport logistics for the delivery of military cargo to the war zone in the conditions of delays and risks is stated and solved. The relevance of the study is related to the analysis of possible losses in the war zone (loss of armed forces, damage and destruction of military equipment, change in hostilities from offensive to defensive, etc.) due to the delayed supply of weapons and military equipment. The study simulates the logistics of transportation in the diverse transport networks to ensure timely delivery of military cargo in the conditions of possible delays and risks that affect the amount of damage in the war zone. Given the complex dynamics of military cargo delivery related to heterogeneity and transshipment in the transport network, the original agent simulation model has been created. This model makes it possible to study the supply process and allows to assess delays, risks and losses. A new algorithm to minimize the delivery time of military cargo, based on the distribution of request clones in a graph representing a heterogeneous transport network is presented. An algorithm to minimize supply risks in wartime that considers long logistics chains for transporting military cargo to the war zone is presented. We study the losses caused by the untimely arrival of various types of military equipment and weapons in the war zone, based on full factorial experiments and the assessments of military experts in the field of military logistics are conducted. Given the contradictions of the criteria of delays, risks and losses, the multi-criteria problem of compromise search optimization based on integer (Boolean) programming is stated and solved. The efficiency of the proposed approach is demonstrated by simulating military cargo supply to the war zone. Alternative supply routes, risks and losses due to delays in supply are analyzed. The choice of the compromise alternative of military cargo delivery route to the war zone is substantiated. The scientific novelty of the study is related to the development of methods and models based on agent simulation, experimental theory and integer optimization, that makes it possible to estimate the delays and losses in the supply of military cargo to the war zone in long logistics chains of diverse transport network. The results of the study can be used to build the optimal routes to supply military cargo in wartime.","PeriodicalId":36122,"journal":{"name":"Radioelectronic and Computer Systems","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44062290","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
D. Chumachenko, Pavlo Pyrohov, I. Meniailov, T. Chumachenko
The COVID-19 pandemic has posed a challenge to public health systems worldwide. As of March 2022, almost 500 million cases have been reported worldwide. More than 6.2 million people died. The war that Russia launched for no reason on the territory of Ukraine is not only the cause of the death of thousands of people and the destruction of dozens of cities but also a large-scale humanitarian crisis. The military invasion also affected the public health sector. The impossibility of providing medical care, non-compliance with sanitary conditions in areas where active hostilities are occurring, high population density during the evacuation, and other factors contribute to a new stage in the spread of COVID-19 in Ukraine. Building an adequate model of the epidemic process will make it possible to assess the actual statistics of the incidence of COVID-19 and assess the risks and effectiveness of measures to curb the curse of the disease epidemic process. The article aims to develop a simulation model of the COVID-19 epidemic process in Ukraine and to study the results of an experimental study in war conditions. The research is targeted at the epidemic process of COVID-19 under military conditions. The subjects of the study are models and methods for modeling the epidemic process based on statistical machine learning methods. To achieve the study's aim, we used forecasting methods and built a model of the COVID-19 epidemic process based on the polynomial regression method. Because of the experiments, the accuracy of predicting new cases of COVID-19 in Ukraine for 30 days was 97,98%, and deaths of COVID-19 in Ukraine – was 99,87%. The model was applied to data on the incidence of COVID-19 in Ukraine for the first month of the war (02/24/22 - 03/25/22). The calculated predictive values showed a significant deviation from the registered statistics. Conclusions. This article describes experimental studies of implementing the COVID-19 epidemic process model in Ukraine based on the polynomial regression method. The constructed model was sufficiently accurate in deciding on anti-epidemic measures to combat the COVID-19 pandemic in the selected area. The study of the model in data on the incidence of COVID-19 in Ukraine during the war made it possible to assess the completeness of the recorded statistics, identify the risks of the spread of COVID-19 in wartime, and determine the necessary measures to curb the epidemic curse of the incidence of COVID-19 in Ukraine. The investigation of the experimental study results shows a significant decrease in the registration of the COVID-19 incidence in Ukraine. An analysis of the situation showed difficulty in accessing medical care, a reduction in diagnosis and registration of new cases, and the war led to the intensification of the COVID-19 epidemic process.
{"title":"Impact of war on COVID-19 pandemic in Ukraine: the simulation study","authors":"D. Chumachenko, Pavlo Pyrohov, I. Meniailov, T. Chumachenko","doi":"10.32620/reks.2022.2.01","DOIUrl":"https://doi.org/10.32620/reks.2022.2.01","url":null,"abstract":"The COVID-19 pandemic has posed a challenge to public health systems worldwide. As of March 2022, almost 500 million cases have been reported worldwide. More than 6.2 million people died. The war that Russia launched for no reason on the territory of Ukraine is not only the cause of the death of thousands of people and the destruction of dozens of cities but also a large-scale humanitarian crisis. The military invasion also affected the public health sector. The impossibility of providing medical care, non-compliance with sanitary conditions in areas where active hostilities are occurring, high population density during the evacuation, and other factors contribute to a new stage in the spread of COVID-19 in Ukraine. Building an adequate model of the epidemic process will make it possible to assess the actual statistics of the incidence of COVID-19 and assess the risks and effectiveness of measures to curb the curse of the disease epidemic process. The article aims to develop a simulation model of the COVID-19 epidemic process in Ukraine and to study the results of an experimental study in war conditions. The research is targeted at the epidemic process of COVID-19 under military conditions. The subjects of the study are models and methods for modeling the epidemic process based on statistical machine learning methods. To achieve the study's aim, we used forecasting methods and built a model of the COVID-19 epidemic process based on the polynomial regression method. Because of the experiments, the accuracy of predicting new cases of COVID-19 in Ukraine for 30 days was 97,98%, and deaths of COVID-19 in Ukraine – was 99,87%. The model was applied to data on the incidence of COVID-19 in Ukraine for the first month of the war (02/24/22 - 03/25/22). The calculated predictive values showed a significant deviation from the registered statistics. Conclusions. This article describes experimental studies of implementing the COVID-19 epidemic process model in Ukraine based on the polynomial regression method. The constructed model was sufficiently accurate in deciding on anti-epidemic measures to combat the COVID-19 pandemic in the selected area. The study of the model in data on the incidence of COVID-19 in Ukraine during the war made it possible to assess the completeness of the recorded statistics, identify the risks of the spread of COVID-19 in wartime, and determine the necessary measures to curb the epidemic curse of the incidence of COVID-19 in Ukraine. The investigation of the experimental study results shows a significant decrease in the registration of the COVID-19 incidence in Ukraine. An analysis of the situation showed difficulty in accessing medical care, a reduction in diagnosis and registration of new cases, and the war led to the intensification of the COVID-19 epidemic process.","PeriodicalId":36122,"journal":{"name":"Radioelectronic and Computer Systems","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47385949","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Subject matter: Estimating the software work is a crucial job of persons participating in software project management. The difficulty in predicting effort is compounded by the fact that software development is always changing. In the past, researchers used one form of development methodology in their work to estimate effort and time. Estimations of the software projects are estimated with different size matrices. The lines of code, story point and use case point are required for the estimation using algorithmic models for procedural, agile, and object-oriented development approaches. Currently, the companies use these three types of size matrices for estimating projects. Not any one model present estimates the effort for different development approaches with different size metrics. This paper proposes a combined software estimation model for three types of development methodologies with regression analysis. The estimation can be done with the proposed model for a software project developed using the procedural, agile, and object-oriented approach. Method: The input for the model is the size of the software, such as lines of code, story point, and use case point. The model is developed using the polynomial regression. The model is developed with the four constant parameters that are based on the procedural, agile, and object-oriented projects. A dataset of python projects for procedural, zia dataset for agile, company dataset for object-oriented methodology is used to propose the model. Conclusion: The effort is predicted for the procedural, agile, and object-oriented projects with the polynomial regression model and compare the results to existing models to validate the work. The R2 is used to measure accuracy and the MMRE is used to determine error. The accuracy of the proposed model was higher than 90% and the error was found to be less than 0.05. The results are compared with case-based reasoning and an ensemble model for the procedural approach, linear regression and Bayesian network for the agile approach, and linear and log-linear regression for object-oriented approach. The minimum error and maximum accuracy is achieved compared to these techniques.
{"title":"The combined model for software development effort estimation using polynomial regression for heterogeneous projects","authors":"Amrita Sharma, N. Chaudhary","doi":"10.32620/reks.2022.2.06","DOIUrl":"https://doi.org/10.32620/reks.2022.2.06","url":null,"abstract":"Subject matter: Estimating the software work is a crucial job of persons participating in software project management. The difficulty in predicting effort is compounded by the fact that software development is always changing. In the past, researchers used one form of development methodology in their work to estimate effort and time. Estimations of the software projects are estimated with different size matrices. The lines of code, story point and use case point are required for the estimation using algorithmic models for procedural, agile, and object-oriented development approaches. Currently, the companies use these three types of size matrices for estimating projects. Not any one model present estimates the effort for different development approaches with different size metrics. This paper proposes a combined software estimation model for three types of development methodologies with regression analysis. The estimation can be done with the proposed model for a software project developed using the procedural, agile, and object-oriented approach. Method: The input for the model is the size of the software, such as lines of code, story point, and use case point. The model is developed using the polynomial regression. The model is developed with the four constant parameters that are based on the procedural, agile, and object-oriented projects. A dataset of python projects for procedural, zia dataset for agile, company dataset for object-oriented methodology is used to propose the model. Conclusion: The effort is predicted for the procedural, agile, and object-oriented projects with the polynomial regression model and compare the results to existing models to validate the work. The R2 is used to measure accuracy and the MMRE is used to determine error. The accuracy of the proposed model was higher than 90% and the error was found to be less than 0.05. The results are compared with case-based reasoning and an ensemble model for the procedural approach, linear regression and Bayesian network for the agile approach, and linear and log-linear regression for object-oriented approach. The minimum error and maximum accuracy is achieved compared to these techniques.","PeriodicalId":36122,"journal":{"name":"Radioelectronic and Computer Systems","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44824754","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Serhii Khmelevsky, Ivan Tupitsya, Olga Khmelevska, O. Musienko, M. Parkhomenko, Oleksandr Pershin, Igor Nikora, Yan Borovensky, Oleksandr Yakobinchuk
Subject of study: technologies implemented in modern video coding algorithms to ensure the appropriate level of reliability in the conditions of their compact presentation. The goal is to develop a technology for transforming the alphabet of a video information based on a quantitative criterion while ensuring the required quality in networks. Objectives: to formulate requirements to video images in dynamic video surveillance systems; to analyze the existing factors leading to an imbalance between the compression and quality characteristics of existing video coding algorithms; to develop a technology for transforming the alphabet of a video information based on a quantitative criterion (attribute) for the best presentation of the encoded data; to develop a mathematical model for the formation of a quantitativeindicator for the transformation of the video images; to analyze the effectiveness of using the developed mathematical model for the formation of a quantitative indicator to provide the required trustworthiness of data for the video information resource; to assess the effectiveness of the developed technology for transforming the original message in terms of a quantitative indicator to ensure the best presentation of the encoded data; to investigate the dynamics of the probabilistic and statistical characteristics of the original message as a result of transformation according to the quantitative criterion of the significance of the elements. The research methods: compression coding methods implemented on the basis of the JPEG algorithms. The research results: a new approach has been proposed based on the transformation of the encoded alphabet of data by use of a quantitative criterion. A mathematical model has been developed for the formation of a quantitative attributethat determines the significance of the elements of the original message. Conclusions. A technology has been developed for transforming the alphabet of the original message, which allows creating conditions for a more profitable presentation of the encoded data due to a significant increase in the dynamic range of probabilistic and statistical characteristics for the transformed message while ensuring the required level of video image quality.
{"title":"Method for quantitative criterion based transformation of the video information alphabet","authors":"Serhii Khmelevsky, Ivan Tupitsya, Olga Khmelevska, O. Musienko, M. Parkhomenko, Oleksandr Pershin, Igor Nikora, Yan Borovensky, Oleksandr Yakobinchuk","doi":"10.32620/reks.2022.2.16","DOIUrl":"https://doi.org/10.32620/reks.2022.2.16","url":null,"abstract":"Subject of study: technologies implemented in modern video coding algorithms to ensure the appropriate level of reliability in the conditions of their compact presentation. The goal is to develop a technology for transforming the alphabet of a video information based on a quantitative criterion while ensuring the required quality in networks. Objectives: to formulate requirements to video images in dynamic video surveillance systems; to analyze the existing factors leading to an imbalance between the compression and quality characteristics of existing video coding algorithms; to develop a technology for transforming the alphabet of a video information based on a quantitative criterion (attribute) for the best presentation of the encoded data; to develop a mathematical model for the formation of a quantitativeindicator for the transformation of the video images; to analyze the effectiveness of using the developed mathematical model for the formation of a quantitative indicator to provide the required trustworthiness of data for the video information resource; to assess the effectiveness of the developed technology for transforming the original message in terms of a quantitative indicator to ensure the best presentation of the encoded data; to investigate the dynamics of the probabilistic and statistical characteristics of the original message as a result of transformation according to the quantitative criterion of the significance of the elements. The research methods: compression coding methods implemented on the basis of the JPEG algorithms. The research results: a new approach has been proposed based on the transformation of the encoded alphabet of data by use of a quantitative criterion. A mathematical model has been developed for the formation of a quantitative attributethat determines the significance of the elements of the original message. Conclusions. A technology has been developed for transforming the alphabet of the original message, which allows creating conditions for a more profitable presentation of the encoded data due to a significant increase in the dynamic range of probabilistic and statistical characteristics for the transformed message while ensuring the required level of video image quality.","PeriodicalId":36122,"journal":{"name":"Radioelectronic and Computer Systems","volume":"21 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41295203","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Sergiy Yakovlev, Oleksii Kartashov, Alexander Mumrienko
To ensure the life of society, it becomes necessary to create systems for monitoring processes or objects using a network of sensors that can control part of the space (territory). Monitoring is understood as a systematic observation of the parameters of an object to obtain information on their compliance with the initial assumptions. Simultaneously, a physical model is constructed that links the characteristics of the object and information about the observation, which making it possible to identify the properties of the object. Such information is based on the processing of signals received using special control sensors. These signals are digitized to provide data on the coverage areas of the sensors. Thus, the physical model is associated with measuring the ability and quality of perception of control sensors, fixing the geometric relationship between them and points in space. The specified physical model corresponds to the geometric statement of the problem of covering the monitoring area with a set of geometric objects, the shape and size of which is determined by the coverage areas of the sensors. With a limited number of sensors, the problem arises of the maximum possible coverage of the area. In this article, we digress from the type of monitoring object and consider the geometric features of coverage problems that arise when designing systems for monitoring a space of various purposes. The current article presents constructive means of mathematical modeling for solving geometric problems of maximum coverage. To formalize the coverage conditions, the concept of constructing the configuration space of geometric objects and a special class of functions are used to establish the dependence of the measure (area, volume) of the coverage configuration on the placement parameters of the covering objects. Since it is extremely difficult to obtain an analytical form of these functions, an algorithmic approach to their calculation is proposed. The approach was implemented on the Pyton algorithm using the Shapely library. A computational experiment was planned and carried out to establish the dependence of the computation time on the number of geometric objects that make up the coverage configuration. To find the maximum coverage, the BFGS local optimization method of the Scipy.optimize package is used. Numerous examples of the implemenation of the proposed approach are given. Conclusions. The article substantiates the use of a software-algorithmic approach for formalization, calculation and optimization of maximum coverage configurations, which makes it possible to effectively solve complex problems of monitoring space and territories.
{"title":"Формалізація та розв'язування задачі максимального покриття області з використанням бібліотеки Shapely для моніторингу територій","authors":"Sergiy Yakovlev, Oleksii Kartashov, Alexander Mumrienko","doi":"10.32620/reks.2022.2.03","DOIUrl":"https://doi.org/10.32620/reks.2022.2.03","url":null,"abstract":"To ensure the life of society, it becomes necessary to create systems for monitoring processes or objects using a network of sensors that can control part of the space (territory). Monitoring is understood as a systematic observation of the parameters of an object to obtain information on their compliance with the initial assumptions. Simultaneously, a physical model is constructed that links the characteristics of the object and information about the observation, which making it possible to identify the properties of the object. Such information is based on the processing of signals received using special control sensors. These signals are digitized to provide data on the coverage areas of the sensors. Thus, the physical model is associated with measuring the ability and quality of perception of control sensors, fixing the geometric relationship between them and points in space. The specified physical model corresponds to the geometric statement of the problem of covering the monitoring area with a set of geometric objects, the shape and size of which is determined by the coverage areas of the sensors. With a limited number of sensors, the problem arises of the maximum possible coverage of the area. In this article, we digress from the type of monitoring object and consider the geometric features of coverage problems that arise when designing systems for monitoring a space of various purposes. The current article presents constructive means of mathematical modeling for solving geometric problems of maximum coverage. To formalize the coverage conditions, the concept of constructing the configuration space of geometric objects and a special class of functions are used to establish the dependence of the measure (area, volume) of the coverage configuration on the placement parameters of the covering objects. Since it is extremely difficult to obtain an analytical form of these functions, an algorithmic approach to their calculation is proposed. The approach was implemented on the Pyton algorithm using the Shapely library. A computational experiment was planned and carried out to establish the dependence of the computation time on the number of geometric objects that make up the coverage configuration. To find the maximum coverage, the BFGS local optimization method of the Scipy.optimize package is used. Numerous examples of the implemenation of the proposed approach are given. Conclusions. The article substantiates the use of a software-algorithmic approach for formalization, calculation and optimization of maximum coverage configurations, which makes it possible to effectively solve complex problems of monitoring space and territories.","PeriodicalId":36122,"journal":{"name":"Radioelectronic and Computer Systems","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42079615","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The subject of the article is a variant of an efficient algorithm for synthesizing a dual discrete model and controller for tracking a given trajectory of a dynamic nonlinear, nonstationary black box object, using standard procedures for diagonalizing the state matrix, which makes it possible to simplify obtaining control values in numerical form and reduce the number of calculations. The current article presents one the possible solutions to the problem of regulator synthesis to ensure stable development of a given trajectory of motion of a nonlinear, non-stationary object of "black box" type using the concept of dual control. The task was set to simplify the previously proposed synthesis algorithm for the adaptive control of dynamic nonlinear, non-stationary objects using the example of first-order object of the "black box" type, using standard procedures for the diagonalization of the state matrix. An extended state matrix is the basis for obtaining a control model and predicting the behavior of a nonlinear non-stationary object, which in turn makes it possible to effectively use the concept of dual control. Methods used in the work are based on concept of dual control, nonlinear dynamic models, matrix theory, difference equations. Obtained results of this work consist of the development of a version of a dual nonparametric controller of nonstationary nonlinear processes, which has adaptive properties, does not require knowledge of the physics of functioning of the control object, is presented in the form of a simple algebraic formula that does not contain coefficients that require adjustment. Conclusion. Scientific novelty lies in the application of each interval matrix operator control for the diagonalization of the state submatrix. This operator is used for subsequent calculation of the control action. This approach enables the use of a standard diagonalization procedure using mathematical applications. The results are presented in the form of a final formula that does not require use of matrix operations during control, which makes it possible to simplify the synthesis of the controller using standard mathematical procedures.
{"title":"Algorithm for the synthesis of dual non-parametric control of \"black box\" type dynamic object with use state matrix diagonalization method","authors":"Anatoliy Zhosan, I. Marynych, O. Serdiuk","doi":"10.32620/reks.2022.2.02","DOIUrl":"https://doi.org/10.32620/reks.2022.2.02","url":null,"abstract":"The subject of the article is a variant of an efficient algorithm for synthesizing a dual discrete model and controller for tracking a given trajectory of a dynamic nonlinear, nonstationary black box object, using standard procedures for diagonalizing the state matrix, which makes it possible to simplify obtaining control values in numerical form and reduce the number of calculations. The current article presents one the possible solutions to the problem of regulator synthesis to ensure stable development of a given trajectory of motion of a nonlinear, non-stationary object of \"black box\" type using the concept of dual control. The task was set to simplify the previously proposed synthesis algorithm for the adaptive control of dynamic nonlinear, non-stationary objects using the example of first-order object of the \"black box\" type, using standard procedures for the diagonalization of the state matrix. An extended state matrix is the basis for obtaining a control model and predicting the behavior of a nonlinear non-stationary object, which in turn makes it possible to effectively use the concept of dual control. Methods used in the work are based on concept of dual control, nonlinear dynamic models, matrix theory, difference equations. Obtained results of this work consist of the development of a version of a dual nonparametric controller of nonstationary nonlinear processes, which has adaptive properties, does not require knowledge of the physics of functioning of the control object, is presented in the form of a simple algebraic formula that does not contain coefficients that require adjustment. Conclusion. Scientific novelty lies in the application of each interval matrix operator control for the diagonalization of the state submatrix. This operator is used for subsequent calculation of the control action. This approach enables the use of a standard diagonalization procedure using mathematical applications. The results are presented in the form of a final formula that does not require use of matrix operations during control, which makes it possible to simplify the synthesis of the controller using standard mathematical procedures.","PeriodicalId":36122,"journal":{"name":"Radioelectronic and Computer Systems","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48445936","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
T. Martyniuk, B. Krukivskyi, L. Kupershtein, Vitaliy Lukichov
The subject of study in this article is the features of structural organization and functioning of the improved Hamming network as a model of neural network heteroassociative memory for classification by discriminant functions. The goal is to improve the neural network classifier based on the Hamming network, which implements the criterion of maximum similarity using discriminant functions and does not have restrictions on the representation of input data (not only binary data). The tasks: analyze the capabilities of associative memory models using neural networks as an example; analyze the features of classification on the principles of discriminant analysis; develop the structure of a neural network classifier as a model of neural network heteroassociative memory; perform simulation modeling of the classification process on the example of medical diagnosis. The methods used are a mathematical model of the functioning of a neural network as a classifier, and simulation in C#. The following results have been obtained: the structure of the neural network classifier has been improved through the formation connection matrix of a hidden layer from pre-calculated coefficients of linear discriminant functions, and the connection matrix of the output layer in the form symmetrical matrix with zeros on the main diagonal. This allows not only to simplify m connections, where m is the number of classes, in the structure of the output layer of the neural network classifier, but also to speed up the classification process, as well as to implement classification by the maximum of discriminant functions. Conclusions. The scientific novelty of the results obtained is as follows: the neural network classification method has been improved using pre-calculated elements of the connection matrices in the hidden and output layers of the classifier, which does not imply a long process of direct neural network learning with using discriminant functions; the structural organization of a neural network classifier is proposed, which is an improvement of the Hamming network as a model of heteroassociative memory, that allows using this classifier in a decision support system for medical diagnosis; the removal of positive feedback in neurons of the competitive (output) layer is implemented, which allows not only simplifies the structure of the neural network classifier but also speeds up the classification process almost 2 times, which is confirmed by the simulation results.
{"title":"Neural network model of heteroassociative memory for the classification task","authors":"T. Martyniuk, B. Krukivskyi, L. Kupershtein, Vitaliy Lukichov","doi":"10.32620/reks.2022.2.09","DOIUrl":"https://doi.org/10.32620/reks.2022.2.09","url":null,"abstract":"The subject of study in this article is the features of structural organization and functioning of the improved Hamming network as a model of neural network heteroassociative memory for classification by discriminant functions. The goal is to improve the neural network classifier based on the Hamming network, which implements the criterion of maximum similarity using discriminant functions and does not have restrictions on the representation of input data (not only binary data). The tasks: analyze the capabilities of associative memory models using neural networks as an example; analyze the features of classification on the principles of discriminant analysis; develop the structure of a neural network classifier as a model of neural network heteroassociative memory; perform simulation modeling of the classification process on the example of medical diagnosis. The methods used are a mathematical model of the functioning of a neural network as a classifier, and simulation in C#. The following results have been obtained: the structure of the neural network classifier has been improved through the formation connection matrix of a hidden layer from pre-calculated coefficients of linear discriminant functions, and the connection matrix of the output layer in the form symmetrical matrix with zeros on the main diagonal. This allows not only to simplify m connections, where m is the number of classes, in the structure of the output layer of the neural network classifier, but also to speed up the classification process, as well as to implement classification by the maximum of discriminant functions. Conclusions. The scientific novelty of the results obtained is as follows: the neural network classification method has been improved using pre-calculated elements of the connection matrices in the hidden and output layers of the classifier, which does not imply a long process of direct neural network learning with using discriminant functions; the structural organization of a neural network classifier is proposed, which is an improvement of the Hamming network as a model of heteroassociative memory, that allows using this classifier in a decision support system for medical diagnosis; the removal of positive feedback in neurons of the competitive (output) layer is implemented, which allows not only simplifies the structure of the neural network classifier but also speeds up the classification process almost 2 times, which is confirmed by the simulation results.","PeriodicalId":36122,"journal":{"name":"Radioelectronic and Computer Systems","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48624790","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
S. Danshyna, A. Nechausov, S. Andrieiev, Valeriy Cheranovskiy
The subject of study in this article is the process of analyzing infrastructure objects for waste management. The current article increases the objectivity of waste management infrastructure objects estimated by developing a model and method of information technology for analyzing several indicators of these objects based on the use of spatially distributed data. Objectives: to analyze the key factors affecting the waste management infrastructure (WMI) to select possible ways to improve the efficiency of its functioning; to develop a model of the WMI objects analyzing process, which determines the structure of information technology for analyzing several indicators of these objects using spatially distributed data; to improve the method of identification and verification of data about WMI objects. The following results were obtained. An approach to the estimation of WMI objects based on set-theoretical and functional modeling of the process of analyzing these objects is proposed. The method for identifying and verifying data about WMI objects has been improved, based on considering them in the form of geographical objects, considering current cartographic and satellite data, which, in contrast to the existing ones, will allow an objective assessment of their compliance with legal and construction standards. For the first time, the structure of information technology for analyzing several indicators of WMI objects is proposed, the use of which in decision support systems will make objective judgments about the existing infrastructure based on spatial data using geoinformation systems. Conclusions. The results of the bibliographic research confirmed that effective monitoring of WMI objects to ensure compliance with legislation in the field of waste management is extremely difficult. This process requires the development of specialized models and methods focused on the use of geoinformation systems for their implementation in decision support systems. Scientific and methodological support of information technology for analyzing several indicators of WMI objects has been developed. Its usage in the tasks of estimating the state of the corresponding objects of the Kharkiv region confirmed that many of them do not meet the existing legal and building requirements, which requires close attention to the problem of waste management and the development of appropriate management decisions.
{"title":"Information technology for analysis of waste management objects infrastructure","authors":"S. Danshyna, A. Nechausov, S. Andrieiev, Valeriy Cheranovskiy","doi":"10.32620/reks.2022.2.08","DOIUrl":"https://doi.org/10.32620/reks.2022.2.08","url":null,"abstract":"The subject of study in this article is the process of analyzing infrastructure objects for waste management. The current article increases the objectivity of waste management infrastructure objects estimated by developing a model and method of information technology for analyzing several indicators of these objects based on the use of spatially distributed data. Objectives: to analyze the key factors affecting the waste management infrastructure (WMI) to select possible ways to improve the efficiency of its functioning; to develop a model of the WMI objects analyzing process, which determines the structure of information technology for analyzing several indicators of these objects using spatially distributed data; to improve the method of identification and verification of data about WMI objects. The following results were obtained. An approach to the estimation of WMI objects based on set-theoretical and functional modeling of the process of analyzing these objects is proposed. The method for identifying and verifying data about WMI objects has been improved, based on considering them in the form of geographical objects, considering current cartographic and satellite data, which, in contrast to the existing ones, will allow an objective assessment of their compliance with legal and construction standards. For the first time, the structure of information technology for analyzing several indicators of WMI objects is proposed, the use of which in decision support systems will make objective judgments about the existing infrastructure based on spatial data using geoinformation systems. Conclusions. The results of the bibliographic research confirmed that effective monitoring of WMI objects to ensure compliance with legislation in the field of waste management is extremely difficult. This process requires the development of specialized models and methods focused on the use of geoinformation systems for their implementation in decision support systems. Scientific and methodological support of information technology for analyzing several indicators of WMI objects has been developed. Its usage in the tasks of estimating the state of the corresponding objects of the Kharkiv region confirmed that many of them do not meet the existing legal and building requirements, which requires close attention to the problem of waste management and the development of appropriate management decisions.","PeriodicalId":36122,"journal":{"name":"Radioelectronic and Computer Systems","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43333276","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
L. Ozirkovskyy, B. Volochiy, O. Shkiliuk, M. Zmysnyi, Pavlo Kazan
The subject of research is to determine the functional safety indicators of a fault-tolerant safety-critical system, namely, the minimal cut sets’ probability for a given duration of the system’s operation, using the state transition diagram (STD). The aim is to create a new method for analyzing the functional safety of a fault-tolerant safety-critical system. This method is based on the methodology of developing models of operational reliability behavior in the form of STD. This methodology provides a detailed representation of inoperable states and their relation with pre-failure (inoperable critical) states. The task is to propose a new classification for inoperable states of the STD to obtain all possible emergencies in the same space of inoperable states. This approach allows consideration the correlations between the failures, that it is impossible to use the fault trees. Since the space of inoperable states can reach hundreds and thousands of states, a method is proposed for their automated determination according to the classification. The state space method was used to conduct the validation of the method of functional safety analysis. The following results were obtained: the system of Chapman-Kolmogorov differential equations is formed in accordance with the STD and it provides the dependence of the functional safety indicator – the minimal cut sets’ probability as a function of the operational duration of the fault-tolerant safety-critical system. This dependence is called the emergency function. The method for determining the emergency function is based on the usage of the emergency mask. Note that the proposed model of operational reliability behavior in the form of STD provides the possibility to conduct both the functional safety and the reliability indicators. The value of the minimal cut sets’ probability for a given duration of operation is determined using the fault tree for the validation of the proposed method of functional safety analysis. The fault tree was built by Reliasoft BlockSim software. The obtained value coincides with the value of the minimal cut sets’ probability, which was defined by the emergency function for the same operational duration. Thus, the designer can comprehensively analyze the feasibility of introducing redundancy (structural, temporal, functional). Conclusions: the scientific novelty of the obtained results is the following: the new method for determining safe, critical and catastrophic states in the set of inoperable states is used in the methodology of the STD developing to obtain the stochastic model of operational reliability behavior of fault-tolerant safety-critical system. This technique ensures an automated defining of emergency function by using an improved structural-automatic model.
{"title":"Functional safety analysis of safety-critical system using state transition diagram","authors":"L. Ozirkovskyy, B. Volochiy, O. Shkiliuk, M. Zmysnyi, Pavlo Kazan","doi":"10.32620/reks.2022.2.12","DOIUrl":"https://doi.org/10.32620/reks.2022.2.12","url":null,"abstract":"The subject of research is to determine the functional safety indicators of a fault-tolerant safety-critical system, namely, the minimal cut sets’ probability for a given duration of the system’s operation, using the state transition diagram (STD). The aim is to create a new method for analyzing the functional safety of a fault-tolerant safety-critical system. This method is based on the methodology of developing models of operational reliability behavior in the form of STD. This methodology provides a detailed representation of inoperable states and their relation with pre-failure (inoperable critical) states. The task is to propose a new classification for inoperable states of the STD to obtain all possible emergencies in the same space of inoperable states. This approach allows consideration the correlations between the failures, that it is impossible to use the fault trees. Since the space of inoperable states can reach hundreds and thousands of states, a method is proposed for their automated determination according to the classification. The state space method was used to conduct the validation of the method of functional safety analysis. The following results were obtained: the system of Chapman-Kolmogorov differential equations is formed in accordance with the STD and it provides the dependence of the functional safety indicator – the minimal cut sets’ probability as a function of the operational duration of the fault-tolerant safety-critical system. This dependence is called the emergency function. The method for determining the emergency function is based on the usage of the emergency mask. Note that the proposed model of operational reliability behavior in the form of STD provides the possibility to conduct both the functional safety and the reliability indicators. The value of the minimal cut sets’ probability for a given duration of operation is determined using the fault tree for the validation of the proposed method of functional safety analysis. The fault tree was built by Reliasoft BlockSim software. The obtained value coincides with the value of the minimal cut sets’ probability, which was defined by the emergency function for the same operational duration. Thus, the designer can comprehensively analyze the feasibility of introducing redundancy (structural, temporal, functional). Conclusions: the scientific novelty of the obtained results is the following: the new method for determining safe, critical and catastrophic states in the set of inoperable states is used in the methodology of the STD developing to obtain the stochastic model of operational reliability behavior of fault-tolerant safety-critical system. This technique ensures an automated defining of emergency function by using an improved structural-automatic model.","PeriodicalId":36122,"journal":{"name":"Radioelectronic and Computer Systems","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47704991","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The subject of research- the process of human skeletal muscles electrical stimulation during medical therapy. The subject of the study is a mathematical model of electrostimulation characteristics, which links the amplitude of muscle contraction and the stimulating effect amplitude. The current work develops a mathematical model in the form of an analytical expression to describe the muscle contraction amplitude dependence on electrical stimulus amplitude. Tasks to be solved: to analyze the dependence peculiarity of muscle contraction amplitude in stimulating impulse amplitude; conduct structural and parametric identification of the model; compare the results obtained using practical data, evaluate the model accuracy; use the obtained model for analytical description with the aim of a priori determination of the optimal stimulus amplitude. Methods used mathematical modeling method, methods of structural and parametric identification of models, approximation methods, parametric optimization methods, mathematical analysis methods. Results obtained an analytical model in the form of a 5th degree polynomial is proposed, which reflects the dependence of muscle contraction amplitude in the stimulus amplitude; the degree of the polynomial is selected and the coefficients of the model are obtained using parametric optimization; a model trajectory was built and the accuracy of modeling was estimated; an equation was obtained and its possible solutions were found to determine the optimal value of the stimulus amplitude; the practical application of the research results was substantiated. The results obtained can be used in the selection of individual effects of electrical stimulation during one session, as well as with extrapolation during the entire rehabilitation process. Scientific novelty: an analytical description showing the dependence of skeletal muscle contraction amplitude on the electrical stimulus amplitude was obtained, which allows determining individual optimal parameters of electromyostimulation.
{"title":"Modeling of electrostimulation characteristics to determine the optimal amplitude of current stimuli","authors":"Olha Yeroshenko, I. Prasol, M. Suknov","doi":"10.32620/reks.2022.2.15","DOIUrl":"https://doi.org/10.32620/reks.2022.2.15","url":null,"abstract":"The subject of research- the process of human skeletal muscles electrical stimulation during medical therapy. The subject of the study is a mathematical model of electrostimulation characteristics, which links the amplitude of muscle contraction and the stimulating effect amplitude. The current work develops a mathematical model in the form of an analytical expression to describe the muscle contraction amplitude dependence on electrical stimulus amplitude. Tasks to be solved: to analyze the dependence peculiarity of muscle contraction amplitude in stimulating impulse amplitude; conduct structural and parametric identification of the model; compare the results obtained using practical data, evaluate the model accuracy; use the obtained model for analytical description with the aim of a priori determination of the optimal stimulus amplitude. Methods used mathematical modeling method, methods of structural and parametric identification of models, approximation methods, parametric optimization methods, mathematical analysis methods. Results obtained an analytical model in the form of a 5th degree polynomial is proposed, which reflects the dependence of muscle contraction amplitude in the stimulus amplitude; the degree of the polynomial is selected and the coefficients of the model are obtained using parametric optimization; a model trajectory was built and the accuracy of modeling was estimated; an equation was obtained and its possible solutions were found to determine the optimal value of the stimulus amplitude; the practical application of the research results was substantiated. The results obtained can be used in the selection of individual effects of electrical stimulation during one session, as well as with extrapolation during the entire rehabilitation process. Scientific novelty: an analytical description showing the dependence of skeletal muscle contraction amplitude on the electrical stimulus amplitude was obtained, which allows determining individual optimal parameters of electromyostimulation.","PeriodicalId":36122,"journal":{"name":"Radioelectronic and Computer Systems","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42987310","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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