Pub Date : 2022-01-30DOI: 10.37791/2687-0649-2022-17-1-55-68
A. Puchkov, E. Lobaneva, Oleg P. Kultygin
Within the framework of the concept of a circular economy, research in the field of creating technological systems for recycling waste from mining and processing plants occupies one of the key positions. This is connected, on the one hand, with significant volumes of such waste, reaching tens of millions of tons and posing a significant environmental hazard to air and water basins, human health, and, on the other hand, with their rich chemical and mineralogical composition, which makes it possible to call them accumulations of technogenic deposits. In this regard, the task of creating control systems for technological processes of processing such waste and their information support, including support for all stages of the passage of information processes, is urgent. The novelty of the presented research lies in the proposed structure of an intelligent control system for a complex chemical and energy technological system for processing apatite-nepheline ores, as well as in an algorithm for predicting technological parameters, which is part of the information support of the control system under consideration. The algorithm is based on the use of the apparatus of deep recurrent neural networks and Kalman filtering, which is used at the stage of data preprocessing to train the neural network. The paper describes the proposed algorithm for predicting multidimensional time series, adapted to the considered technological process, presents the software executed in the MatLab environment to demonstrate the efficiency of the specified combination of methods for processing technological parameters. In a model experiment, it has been shown that the use of filtering makes it possible to increase the accuracy of the forecast, which is especially noticeable at its large horizons. The practical significance of the research results is the proposed structure of an intelligent control system for the processing of apatite-nepheline ore waste and software for predicting its parameters, which can be used in various decision support systems.
{"title":"Algorithm for predicting the parameters of a system for processing waste apatite-nepheline ores","authors":"A. Puchkov, E. Lobaneva, Oleg P. Kultygin","doi":"10.37791/2687-0649-2022-17-1-55-68","DOIUrl":"https://doi.org/10.37791/2687-0649-2022-17-1-55-68","url":null,"abstract":"Within the framework of the concept of a circular economy, research in the field of creating technological systems for recycling waste from mining and processing plants occupies one of the key positions. This is connected, on the one hand, with significant volumes of such waste, reaching tens of millions of tons and posing a significant environmental hazard to air and water basins, human health, and, on the other hand, with their rich chemical and mineralogical composition, which makes it possible to call them accumulations of technogenic deposits. In this regard, the task of creating control systems for technological processes of processing such waste and their information support, including support for all stages of the passage of information processes, is urgent. The novelty of the presented research lies in the proposed structure of an intelligent control system for a complex chemical and energy technological system for processing apatite-nepheline ores, as well as in an algorithm for predicting technological parameters, which is part of the information support of the control system under consideration. The algorithm is based on the use of the apparatus of deep recurrent neural networks and Kalman filtering, which is used at the stage of data preprocessing to train the neural network. The paper describes the proposed algorithm for predicting multidimensional time series, adapted to the considered technological process, presents the software executed in the MatLab environment to demonstrate the efficiency of the specified combination of methods for processing technological parameters. In a model experiment, it has been shown that the use of filtering makes it possible to increase the accuracy of the forecast, which is especially noticeable at its large horizons. The practical significance of the research results is the proposed structure of an intelligent control system for the processing of apatite-nepheline ore waste and software for predicting its parameters, which can be used in various decision support systems.","PeriodicalId":44195,"journal":{"name":"Journal of Applied Mathematics & Informatics","volume":"61 1","pages":""},"PeriodicalIF":0.3,"publicationDate":"2022-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78896546","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}
Pub Date : 2022-01-30DOI: 10.37791/2687-0649-2022-17-1-109-116
O. Bulygina, E. Vlasova
In recent years, simulation has been actively used to study socio-economic processes in order to test various management decisions (for analyzing risks, projects, regional processes, logistics, etc.). Today, three simulation systems (Actor Pilgrim, AnyLogic, GPSS World), each of which has its own areas of application, are the most widespread in Russia. So, the system Actor Pilgrim is most suitable for modeling socio- economic processes. The first version of this system was developed by a group led by Professor Alexander Anatolyevich Yemelyanov more than 35 years ago to solve experimental problems in the direction of "Flexible automated production". It was based on a new modeling paradigm, which was built on the actor-network theory. The transition to solving new problems, primarily in the economics, led to the need for its further system development through the implementation of temporal, financial and spatial dynamics. Currently, the system development is carried out through the construction of hybrid simulation models, which is associated with the introduction of various analysis methods. So, when modeling actual technical and economic processes (for example, import substitution of high- tech products), it is proposed to use artificial intelligence methods that allow you to get informed decisions in conditions of information uncertainty. Models that include fuzzy logic methods and swarm algorithms (in particular, bacterial optimization) have shown good results. For example, fuzzy logic methods have been used to assign "fair" priorities to option projects through a detailed analysis of the factors of the internal and external environment of enterprises that will implement them. Bacterial optimization algorithms have been used to search for "promising" areas for the implementation of the projects of import substitution of high-tech products. These swarm algorithms are distinguished by the ability to simultaneously study favorable and negative factors, i. e. allow taking into account various risk situations. The modern version of Actor Pilgrim is intended for systems analysts, economists-mathematicians and other professionals who are familiar with programming, but are not professional programmers.
{"title":"Features of building hybrid simulation models in Actor Pilgrim","authors":"O. Bulygina, E. Vlasova","doi":"10.37791/2687-0649-2022-17-1-109-116","DOIUrl":"https://doi.org/10.37791/2687-0649-2022-17-1-109-116","url":null,"abstract":"In recent years, simulation has been actively used to study socio-economic processes in order to test various management decisions (for analyzing risks, projects, regional processes, logistics, etc.). Today, three simulation systems (Actor Pilgrim, AnyLogic, GPSS World), each of which has its own areas of application, are the most widespread in Russia. So, the system Actor Pilgrim is most suitable for modeling socio- economic processes. The first version of this system was developed by a group led by Professor Alexander Anatolyevich Yemelyanov more than 35 years ago to solve experimental problems in the direction of \"Flexible automated production\". It was based on a new modeling paradigm, which was built on the actor-network theory. The transition to solving new problems, primarily in the economics, led to the need for its further system development through the implementation of temporal, financial and spatial dynamics. Currently, the system development is carried out through the construction of hybrid simulation models, which is associated with the introduction of various analysis methods. So, when modeling actual technical and economic processes (for example, import substitution of high- tech products), it is proposed to use artificial intelligence methods that allow you to get informed decisions in conditions of information uncertainty. Models that include fuzzy logic methods and swarm algorithms (in particular, bacterial optimization) have shown good results. For example, fuzzy logic methods have been used to assign \"fair\" priorities to option projects through a detailed analysis of the factors of the internal and external environment of enterprises that will implement them. Bacterial optimization algorithms have been used to search for \"promising\" areas for the implementation of the projects of import substitution of high-tech products. These swarm algorithms are distinguished by the ability to simultaneously study favorable and negative factors, i. e. allow taking into account various risk situations. The modern version of Actor Pilgrim is intended for systems analysts, economists-mathematicians and other professionals who are familiar with programming, but are not professional programmers.","PeriodicalId":44195,"journal":{"name":"Journal of Applied Mathematics & Informatics","volume":"27 1","pages":""},"PeriodicalIF":0.3,"publicationDate":"2022-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80433974","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}
Pub Date : 2022-01-30DOI: 10.37791/2687-0649-2022-17-1-97-108
L. Gadasina, A. Vedernikova, M. Ivanova
The geographical location and tourist features of St. Petersburg require a specialized web service for owners and tenants of river transport, aggregating all the information necessary for them. Currently, such information is available in various news sources, web portals and groups in social networks. The work presents a prototype of a service for small river transport users. Information needs and functional and requirements for it were identified during in-depth interviews with stakeholders of the project. The web service database is implemented in the PostgreSQL DBMS with the PostGIS extension. The work presents the structure of the service, which includes 10 pages, describes its main sections, such as current regulatory documents, news, interactive maps, reference information, as well as technical information about ships and restrictions on their movement due to technical characteristics. During its development, an analysis of existing solutions related to each section was carried out. During the "Maps" section development, an analysis of existing web tools for displaying interactive maps and the selection of the best solutions was carried out. Using the Google Maps designer, interactive maps were created for the web service being developed. The first of them is a map of the city's water bodies, containing such layers as: floating gas stations, lighthouses, customs, checkpoint and Ministry of Emergencies, private yacht clubs and marinas, berths and quayes, bridges, etc. The interactive weather map allows the user to get acquainted with the weather conditions, as well as their 5-day forecast. One of the priority functional requirements of the web service, called stakeholders, was the determination of water barriers and bridges that were inappropriate in the size of the vessel. The "Your Ship" section of the developed prototype web service offers a solution to meet this requirement. The developed web service is one of the favorable incentives for the development of the water tourism sphere and the use of river transport in St. Petersburg.
{"title":"Web-service development for owners of small river transport in Saint Petersburg","authors":"L. Gadasina, A. Vedernikova, M. Ivanova","doi":"10.37791/2687-0649-2022-17-1-97-108","DOIUrl":"https://doi.org/10.37791/2687-0649-2022-17-1-97-108","url":null,"abstract":"The geographical location and tourist features of St. Petersburg require a specialized web service for owners and tenants of river transport, aggregating all the information necessary for them. Currently, such information is available in various news sources, web portals and groups in social networks. The work presents a prototype of a service for small river transport users. Information needs and functional and requirements for it were identified during in-depth interviews with stakeholders of the project. The web service database is implemented in the PostgreSQL DBMS with the PostGIS extension. The work presents the structure of the service, which includes 10 pages, describes its main sections, such as current regulatory documents, news, interactive maps, reference information, as well as technical information about ships and restrictions on their movement due to technical characteristics. During its development, an analysis of existing solutions related to each section was carried out. During the \"Maps\" section development, an analysis of existing web tools for displaying interactive maps and the selection of the best solutions was carried out. Using the Google Maps designer, interactive maps were created for the web service being developed. The first of them is a map of the city's water bodies, containing such layers as: floating gas stations, lighthouses, customs, checkpoint and Ministry of Emergencies, private yacht clubs and marinas, berths and quayes, bridges, etc. The interactive weather map allows the user to get acquainted with the weather conditions, as well as their 5-day forecast. One of the priority functional requirements of the web service, called stakeholders, was the determination of water barriers and bridges that were inappropriate in the size of the vessel. The \"Your Ship\" section of the developed prototype web service offers a solution to meet this requirement. The developed web service is one of the favorable incentives for the development of the water tourism sphere and the use of river transport in St. Petersburg.","PeriodicalId":44195,"journal":{"name":"Journal of Applied Mathematics & Informatics","volume":"1 1","pages":""},"PeriodicalIF":0.3,"publicationDate":"2022-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79900232","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}
Pub Date : 2022-01-30DOI: 10.37791/2687-0649-2022-17-1-19-26
A. A. Evstifeev
The issues of information support for decision-making during periodic maintenance of gas-cylinder equipment of vehicles running on natural gas, ensuring safe operation, contributing to an increase in the efficiency of transportation of goods and goods: reducing vehicle downtime due to failure of the fuel system using gas fuel by 10–18%; reducing the likelihood of functioning of gas equipment in hazardous modes by 12–17%. The technical requirements for gas equipment and procedures for its periodic maintenance are formulated. The concept of the formation and application of a unified state register of gas equipment, which is a tool for limiting admission to the turnover of products that does not meet regulatory and market requirements, is proposed. An information-logical model of decision-making support has been developed, which allows, depending on the current technical condition of assemblies and parts, based on the specified requirements for the duration of the period between maintenance, to propose the best option for carrying out diagnostic, repair and commissioning measures for gas-cylinder equipment of vehicles. The procedure for the formation of an extended list of measures for periodic maintenance of gas equipment is presented on the example of individual nodes of the fuel system of a vehicle running on compressed natural gas. The software implementation of the information- logical model is carried out in the form of a plug-in extension to the database core of the decision support information system for the operation of gas equipment, implemented on the Oracle database management system with integrated support for the high-level object- oriented language Java. For the convenience of working with the information-logical model, a computational and analytical module of the information system for decision-making support during the operation of gas-cylinder equipment with elements of fuzzy logic has been developed. The model was tested on the example of the implementation of measures during the periodic maintenance of the gas equipment of the KamAZ 65116 truck.
{"title":"Information decision-making support for periodic maintenance of gas balloon equipment","authors":"A. A. Evstifeev","doi":"10.37791/2687-0649-2022-17-1-19-26","DOIUrl":"https://doi.org/10.37791/2687-0649-2022-17-1-19-26","url":null,"abstract":"The issues of information support for decision-making during periodic maintenance of gas-cylinder equipment of vehicles running on natural gas, ensuring safe operation, contributing to an increase in the efficiency of transportation of goods and goods: reducing vehicle downtime due to failure of the fuel system using gas fuel by 10–18%; reducing the likelihood of functioning of gas equipment in hazardous modes by 12–17%. The technical requirements for gas equipment and procedures for its periodic maintenance are formulated. The concept of the formation and application of a unified state register of gas equipment, which is a tool for limiting admission to the turnover of products that does not meet regulatory and market requirements, is proposed. An information-logical model of decision-making support has been developed, which allows, depending on the current technical condition of assemblies and parts, based on the specified requirements for the duration of the period between maintenance, to propose the best option for carrying out diagnostic, repair and commissioning measures for gas-cylinder equipment of vehicles. The procedure for the formation of an extended list of measures for periodic maintenance of gas equipment is presented on the example of individual nodes of the fuel system of a vehicle running on compressed natural gas. The software implementation of the information- logical model is carried out in the form of a plug-in extension to the database core of the decision support information system for the operation of gas equipment, implemented on the Oracle database management system with integrated support for the high-level object- oriented language Java. For the convenience of working with the information-logical model, a computational and analytical module of the information system for decision-making support during the operation of gas-cylinder equipment with elements of fuzzy logic has been developed. The model was tested on the example of the implementation of measures during the periodic maintenance of the gas equipment of the KamAZ 65116 truck.","PeriodicalId":44195,"journal":{"name":"Journal of Applied Mathematics & Informatics","volume":"57 1","pages":""},"PeriodicalIF":0.3,"publicationDate":"2022-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75631239","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}
Pub Date : 2022-01-30DOI: 10.37791/2687-0649-2022-17-1-117-129
Olga D. Kosorukova, Nikolay N. Prokimnov
he article 30 of the Federal Law "On the Securities Market" establishes that significant facts are information that, if disclosed, may have a significant impact on the value or quotations of the issuer's securities and (or) on the decision to acquire or alienate the issuer's securities by any interested person acting reasonably and in good faith. At the same time, there are very few empirical studies proving the influence of significant facts on the value or quotations of securities of Russian issuers. Modeling of such influence in order to manage the value and capitalization level of Russian issuers is advisable for investors, owners and management of Russian public joint stock companies to study the possibilities of managing the value and capitalization level of companies. The solution to this problem is based on measuring the results of the joint-stock company's activities and publicly disclosing the information necessary for making managerial decisions, which in the Russian Federation includes, among other things, significant facts. Significant facts are events that can change the current state of the company, in particular, affect such an indicator of its activity as the level of capitalization, therefore, affect the decisions made by the interested person. A few studies on the impact of significant facts on the level of capitalization of Russian companies have already been conducted earlier, however, since their implementation, a number of regulatory documents have come into force that change the legislative environment and affect, among other things, the composition of mandatory registration and disclosure of significant facts. This paper presents the results of a study aimed at establishing a list of the most significant events characteristic of companies' activities, identifying events that are universal in terms of the frequency of occurrence and significance of consequences, and finding out whether there is a connection between their occurrence and the effects caused in the form of changes in the values of financial indicators. For the research, data from 20 large Russian companies representing the oil and gas, metallurgical, chemical and energy industries were used, and received in the form of reports for the period following the introduction of changes in the regulatory environment.
{"title":"Modeling the impact of significant facts on the level of capitalization of Russian companies","authors":"Olga D. Kosorukova, Nikolay N. Prokimnov","doi":"10.37791/2687-0649-2022-17-1-117-129","DOIUrl":"https://doi.org/10.37791/2687-0649-2022-17-1-117-129","url":null,"abstract":"he article 30 of the Federal Law \"On the Securities Market\" establishes that significant facts are information that, if disclosed, may have a significant impact on the value or quotations of the issuer's securities and (or) on the decision to acquire or alienate the issuer's securities by any interested person acting reasonably and in good faith. At the same time, there are very few empirical studies proving the influence of significant facts on the value or quotations of securities of Russian issuers. Modeling of such influence in order to manage the value and capitalization level of Russian issuers is advisable for investors, owners and management of Russian public joint stock companies to study the possibilities of managing the value and capitalization level of companies. The solution to this problem is based on measuring the results of the joint-stock company's activities and publicly disclosing the information necessary for making managerial decisions, which in the Russian Federation includes, among other things, significant facts. Significant facts are events that can change the current state of the company, in particular, affect such an indicator of its activity as the level of capitalization, therefore, affect the decisions made by the interested person. A few studies on the impact of significant facts on the level of capitalization of Russian companies have already been conducted earlier, however, since their implementation, a number of regulatory documents have come into force that change the legislative environment and affect, among other things, the composition of mandatory registration and disclosure of significant facts. This paper presents the results of a study aimed at establishing a list of the most significant events characteristic of companies' activities, identifying events that are universal in terms of the frequency of occurrence and significance of consequences, and finding out whether there is a connection between their occurrence and the effects caused in the form of changes in the values of financial indicators. For the research, data from 20 large Russian companies representing the oil and gas, metallurgical, chemical and energy industries were used, and received in the form of reports for the period following the introduction of changes in the regulatory environment.","PeriodicalId":44195,"journal":{"name":"Journal of Applied Mathematics & Informatics","volume":"17 1 1","pages":""},"PeriodicalIF":0.3,"publicationDate":"2022-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87696155","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}
Pub Date : 2022-01-30DOI: 10.37791/2687-0649-2022-17-1-83-96
M. Tumbinskaya, A. Abzalov
Ensuring information security of automated process control systems (IACS) is a difficult task and its solution requires an integrated approach. Various computer threats need to be considered, which may be external, internal, accidental or deliberate. With the global growth of cybercrimes and the constant improvement of cyberattacks, it is necessary to increase the level of security of IACS, web resources, information systems, etc. Achieving the goal of increasing the level of security is possible by solving the problem of training users to respond to the facts of the implementation of computer threats during the operation of the IACS, i. e. information security incidents. The article describes software, the main task of which is to provide users of an industrial automated system with practical skills for an adequate response to incidents, which will increase the level of users' knowledge in the field of information security. The paper presents an analysis of the information security of an automated process control system, which showed that, on average, in 89.5% of cases, attackers use malicious software to gain access to information unauthorizedly, and on average, in 83% of cases, they use social engineering methods. An industrial automated system of a large enterprise in the machine- building industry of the Republic of Tatarstan was selected for the study. The results of the study and experimental data showed that as a result of training and after it, users more correctly and adequately respond to emerging information security incidents due to the fact that most situations were considered and analyzed during the training period using software. On average, the number of attacks in the analyzed periods as a whole decreased by 28%: the number of attacks carried out using social engineering methods decreased by 51.75%, the number of attacks using malicious software by 40.25%, the number of DoS-type attacks – by 11.75%, the number of credential brute-force attacks – by 7.5%.
{"title":"Investigation of the results of using a soft simulator for responding to the facts of the implementation of computer threats in an automated process control system","authors":"M. Tumbinskaya, A. Abzalov","doi":"10.37791/2687-0649-2022-17-1-83-96","DOIUrl":"https://doi.org/10.37791/2687-0649-2022-17-1-83-96","url":null,"abstract":"Ensuring information security of automated process control systems (IACS) is a difficult task and its solution requires an integrated approach. Various computer threats need to be considered, which may be external, internal, accidental or deliberate. With the global growth of cybercrimes and the constant improvement of cyberattacks, it is necessary to increase the level of security of IACS, web resources, information systems, etc. Achieving the goal of increasing the level of security is possible by solving the problem of training users to respond to the facts of the implementation of computer threats during the operation of the IACS, i. e. information security incidents. The article describes software, the main task of which is to provide users of an industrial automated system with practical skills for an adequate response to incidents, which will increase the level of users' knowledge in the field of information security. The paper presents an analysis of the information security of an automated process control system, which showed that, on average, in 89.5% of cases, attackers use malicious software to gain access to information unauthorizedly, and on average, in 83% of cases, they use social engineering methods. An industrial automated system of a large enterprise in the machine- building industry of the Republic of Tatarstan was selected for the study. The results of the study and experimental data showed that as a result of training and after it, users more correctly and adequately respond to emerging information security incidents due to the fact that most situations were considered and analyzed during the training period using software. On average, the number of attacks in the analyzed periods as a whole decreased by 28%: the number of attacks carried out using social engineering methods decreased by 51.75%, the number of attacks using malicious software by 40.25%, the number of DoS-type attacks – by 11.75%, the number of credential brute-force attacks – by 7.5%.","PeriodicalId":44195,"journal":{"name":"Journal of Applied Mathematics & Informatics","volume":"16 1","pages":""},"PeriodicalIF":0.3,"publicationDate":"2022-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74188832","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}
Pub Date : 2022-01-30DOI: 10.37791/2687-0649-2022-17-1-69-82
A. Sulavko, A. A. Khramov
Open biometric images (fingerprint, iris, face) are "in sight" and therefore compromised in the natural environment. In this work, it is proposed to use data on the internal structure of the outer ear obtained using echography as biometric images. The individual characteristics of the ear canal of subjects are hidden from direct observation and cannot be copied by photographing. The proposed authentication method is based on cepstral analysis of echograms of the ear canal using neural network biometrics to code converters, trained in accordance with GOST R 52633.5. The neural network biometrics-code converter allows you to associate a user's cryptographic key or password with his biometric image. This is a shallow neural network of one or two layers of neurons, which is configured to generate a key specified during training when an image of a known user arrives, and when an unknown image arrives at its inputs, generate a random code with high entropy. At the entrance to this network, cepstral signs of echograms were received. To apply the method in practice, you need a special device that combines a headphone with a sound-proof housing and a microphone. The results obtained can be called optimistic EER = 0.031 (FAR = 0.001 at FRR = 0.23). The use of neural network converters biometrics-code showed a relatively higher percentage of errors in comparison with multilayer neural networks and the naive Bayes classification scheme, however, neural network biometrics to code converters allows you to implement authentication in a protected mode. This means that the subject's biometric data will be protected from compromise at the stages of storage, execution and transmission via communication channels.
{"title":"Biometric authentication method based on cepstral characteristics of external ear echograms and biometrics-to-code neural converter","authors":"A. Sulavko, A. A. Khramov","doi":"10.37791/2687-0649-2022-17-1-69-82","DOIUrl":"https://doi.org/10.37791/2687-0649-2022-17-1-69-82","url":null,"abstract":"Open biometric images (fingerprint, iris, face) are \"in sight\" and therefore compromised in the natural environment. In this work, it is proposed to use data on the internal structure of the outer ear obtained using echography as biometric images. The individual characteristics of the ear canal of subjects are hidden from direct observation and cannot be copied by photographing. The proposed authentication method is based on cepstral analysis of echograms of the ear canal using neural network biometrics to code converters, trained in accordance with GOST R 52633.5. The neural network biometrics-code converter allows you to associate a user's cryptographic key or password with his biometric image. This is a shallow neural network of one or two layers of neurons, which is configured to generate a key specified during training when an image of a known user arrives, and when an unknown image arrives at its inputs, generate a random code with high entropy. At the entrance to this network, cepstral signs of echograms were received. To apply the method in practice, you need a special device that combines a headphone with a sound-proof housing and a microphone. The results obtained can be called optimistic EER = 0.031 (FAR = 0.001 at FRR = 0.23). The use of neural network converters biometrics-code showed a relatively higher percentage of errors in comparison with multilayer neural networks and the naive Bayes classification scheme, however, neural network biometrics to code converters allows you to implement authentication in a protected mode. This means that the subject's biometric data will be protected from compromise at the stages of storage, execution and transmission via communication channels.","PeriodicalId":44195,"journal":{"name":"Journal of Applied Mathematics & Informatics","volume":"26 1","pages":""},"PeriodicalIF":0.3,"publicationDate":"2022-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79514655","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}
Pub Date : 2021-12-24DOI: 10.37791/2687-0649-2021-16-6-6-20
Aleksandr O. Suvorov, Aleksandr A. Petrenko, Anastasija D. Neprina
The article considers a comparative analysis of the effectiveness in use of ARIMA, ARCH, GARCH models, а multi-factor forecasting model, and a decision tree model. Model functionality can be evaluated on the practical examples presented in the article. The results of applying the Dickey-Fuller test according to various data to verify the presence of non- stationarity are obtained. Parametric arguments for the models under study are described. The initial data, the order of the study, the results and charts are presented. Using the R programming language, practical studies focused on the functionality of the technical and fundamental analysis models were carried out to obtain the forecast values of PJSC "Sberbank" stock rate. The software modeling process showed the strengths and weaknesses of each of the models considered. The best results were shown by the multi-factor model. The paper gives quantitative indicators of the forecast values. A comparative table of the statistical indicators showing the results of the forecast models is presented and the conclusions are drawn based on the suitability of their modeling. Current study was carried out to identify models of technical and fundamental analysis that give the most accurate forecast of the stock price with the possibility of further implementation in a computer program.
{"title":"Comparative evaluation of technical and fundamental analysis models when predicting stock prices","authors":"Aleksandr O. Suvorov, Aleksandr A. Petrenko, Anastasija D. Neprina","doi":"10.37791/2687-0649-2021-16-6-6-20","DOIUrl":"https://doi.org/10.37791/2687-0649-2021-16-6-6-20","url":null,"abstract":"The article considers a comparative analysis of the effectiveness in use of ARIMA, ARCH, GARCH models, а multi-factor forecasting model, and a decision tree model. Model functionality can be evaluated on the practical examples presented in the article. The results of applying the Dickey-Fuller test according to various data to verify the presence of non- stationarity are obtained. Parametric arguments for the models under study are described. The initial data, the order of the study, the results and charts are presented. Using the R programming language, practical studies focused on the functionality of the technical and fundamental analysis models were carried out to obtain the forecast values of PJSC \"Sberbank\" stock rate. The software modeling process showed the strengths and weaknesses of each of the models considered. The best results were shown by the multi-factor model. The paper gives quantitative indicators of the forecast values. A comparative table of the statistical indicators showing the results of the forecast models is presented and the conclusions are drawn based on the suitability of their modeling. Current study was carried out to identify models of technical and fundamental analysis that give the most accurate forecast of the stock price with the possibility of further implementation in a computer program.","PeriodicalId":44195,"journal":{"name":"Journal of Applied Mathematics & Informatics","volume":"6 1","pages":""},"PeriodicalIF":0.3,"publicationDate":"2021-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72527497","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}
Pub Date : 2021-12-24DOI: 10.37791/2687-0649-2021-16-6-131-143
Y. Ivanyo, S. Petrova, Margarita N. Barsukova, Yuliana V. Stolopova
The paper considers factor models that allow predicting the yield of agricultural crops. It is shown that the main climatic parameters that affect the effective feature are the air temperature and precipitation during the initial growing season. In this case, the factors of heat supply and moisture supply can represent values for both a month and another interval close to this duration. In addition to air temperature and precipitation, the yield of grain crops is affected by time. Models can reflect the relationship of the effective feature with factors at the level of experimental fields, agricultural organizations, and municipal districts. The presence of significant regression dependencies, which can be linear and nonlinear, reduces the uncertainty of the problem of optimizing agricultural production by reducing random and interval parameters. A model of parametric programming is presented, taking into account the expressions that characterize the relationship between the yield of grain crops and meteorological parameters in two variants, in order to obtain optimal plans for the production of agricultural products by the commodity producer. An example of the implementation of an optimization model for a real economy is considered. The proposed model is designed to support decision-making in conditions of uncertainty. The work is carried out according to statistical data on the yield of wheat, barley and oats in the Usolsky, Cheremkhovsky and Irkutsk districts for 1997-2018; based on the yield of variety plots in the Usolsky, Irkutsk, Bratsky and Nukutsky districts for 2000-2018 according to the data of the State Export Commission; based on the yield of LLC "Sibirskaya Niva" for the period 2005-2018. In addition, daily air temperatures and daily precipitation in the period May–August for 1997-2018 were used for meteorological points: Usolye-Sibirskoye, Cheremkhovo, Irkutsk and Bratsk.
{"title":"Parametric programming problem with crop yield forecasting models","authors":"Y. Ivanyo, S. Petrova, Margarita N. Barsukova, Yuliana V. Stolopova","doi":"10.37791/2687-0649-2021-16-6-131-143","DOIUrl":"https://doi.org/10.37791/2687-0649-2021-16-6-131-143","url":null,"abstract":"The paper considers factor models that allow predicting the yield of agricultural crops. It is shown that the main climatic parameters that affect the effective feature are the air temperature and precipitation during the initial growing season. In this case, the factors of heat supply and moisture supply can represent values for both a month and another interval close to this duration. In addition to air temperature and precipitation, the yield of grain crops is affected by time. Models can reflect the relationship of the effective feature with factors at the level of experimental fields, agricultural organizations, and municipal districts. The presence of significant regression dependencies, which can be linear and nonlinear, reduces the uncertainty of the problem of optimizing agricultural production by reducing random and interval parameters. A model of parametric programming is presented, taking into account the expressions that characterize the relationship between the yield of grain crops and meteorological parameters in two variants, in order to obtain optimal plans for the production of agricultural products by the commodity producer. An example of the implementation of an optimization model for a real economy is considered. The proposed model is designed to support decision-making in conditions of uncertainty. The work is carried out according to statistical data on the yield of wheat, barley and oats in the Usolsky, Cheremkhovsky and Irkutsk districts for 1997-2018; based on the yield of variety plots in the Usolsky, Irkutsk, Bratsky and Nukutsky districts for 2000-2018 according to the data of the State Export Commission; based on the yield of LLC \"Sibirskaya Niva\" for the period 2005-2018. In addition, daily air temperatures and daily precipitation in the period May–August for 1997-2018 were used for meteorological points: Usolye-Sibirskoye, Cheremkhovo, Irkutsk and Bratsk.","PeriodicalId":44195,"journal":{"name":"Journal of Applied Mathematics & Informatics","volume":"99 1","pages":""},"PeriodicalIF":0.3,"publicationDate":"2021-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83333869","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}
Pub Date : 2021-12-24DOI: 10.37791/2687-0649-2021-16-6-43-53
R. Solopov, A. Samulchenkov, Vladislav I. Ziryukin
Evolutionary modeling is one of the areas of artificial intelligence, which essence is the computational processes interpretation and the final forms of integral computational algorithms construction from their existence, variability and development the points of view in natural systems. All evolutionary modeling methods are of an optimization nature due to the basic use of the theory of natural selection principles. One of the most common methods of evolutionary modeling is the genetic algorithm (GA). It is the method of adaptive search for solutions based on the principles of the evolution and the natural selection with the preservation of biological terminology in a simplified form theories. Its essence is to determine the most fit individual (solution) by the value of its fitness function during evolution, considering the analysis of the heredity influences and the external environment. Despite the biological terminology, genetical algorithms are a universal computational tool that can be used to solve a wide range of complex problems, including the electric power industry. The authors considered the issue of the genetic algorithm use in the framework of calculating the steady state of the electrical network (SS EN), since the mathematical electrical network model is a system of high-order nonlinear equations, where all the restrictions imposed by the physical properties of the object under consideration are taken into account. Its solution is a rather laborious optimization problem, due to the operating electrical networks complexity. The correct solution of this system is the most critical stage in the calculation of the SS EN. It is the reason for importance and urgency of the search for SS EN calculating optimal methods task. This paper presents the development results of an analytical apparatus that made it possible to search for a solution to the problem of calculating electrical networks steady-state modes using the genetic algorithm based on special software.
{"title":"Genetic algorithm as a tool for modeling calculations of electric power systems","authors":"R. Solopov, A. Samulchenkov, Vladislav I. Ziryukin","doi":"10.37791/2687-0649-2021-16-6-43-53","DOIUrl":"https://doi.org/10.37791/2687-0649-2021-16-6-43-53","url":null,"abstract":"Evolutionary modeling is one of the areas of artificial intelligence, which essence is the computational processes interpretation and the final forms of integral computational algorithms construction from their existence, variability and development the points of view in natural systems. All evolutionary modeling methods are of an optimization nature due to the basic use of the theory of natural selection principles. One of the most common methods of evolutionary modeling is the genetic algorithm (GA). It is the method of adaptive search for solutions based on the principles of the evolution and the natural selection with the preservation of biological terminology in a simplified form theories. Its essence is to determine the most fit individual (solution) by the value of its fitness function during evolution, considering the analysis of the heredity influences and the external environment. Despite the biological terminology, genetical algorithms are a universal computational tool that can be used to solve a wide range of complex problems, including the electric power industry. The authors considered the issue of the genetic algorithm use in the framework of calculating the steady state of the electrical network (SS EN), since the mathematical electrical network model is a system of high-order nonlinear equations, where all the restrictions imposed by the physical properties of the object under consideration are taken into account. Its solution is a rather laborious optimization problem, due to the operating electrical networks complexity. The correct solution of this system is the most critical stage in the calculation of the SS EN. It is the reason for importance and urgency of the search for SS EN calculating optimal methods task. This paper presents the development results of an analytical apparatus that made it possible to search for a solution to the problem of calculating electrical networks steady-state modes using the genetic algorithm based on special software.","PeriodicalId":44195,"journal":{"name":"Journal of Applied Mathematics & Informatics","volume":"40 1","pages":""},"PeriodicalIF":0.3,"publicationDate":"2021-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77643729","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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