Pub Date : 2022-09-28DOI: 10.1109/ICISCT55600.2022.10146788
N. Mamatov, N. Niyozmatova, A. Samijonov, B. Samijonov
A language model is a set of restrictions on the sequence of words allowed in a given language, and these restrictions can be expressed, for example, by the rules of a generative grammar or by a statistic of each pair of words evaluated in a given language. simple educational building. Although there are words with similar-sounding phonemes, it is usually not difficult for people to recognize the word. It mostly has to do with knowing the context and being very good at what words or phrases might be in it. The purpose of the language model is to provide context to the speech recognition system. The language model determines what words are allowed in the system language and in what order they can occur.Language models are trained, i.e., n-gram probabilities are estimated by observing sequences of words in a text corpus. Confusion reduction is typically performed on training data containing millions of word tokens. But, as has been observed, reducing confusion does not improve speech recognition results. Therefore, algorithms should be used that improve language models in terms of their impact on speech recognition, especially language models that determine the probability distribution of the speaker’s next spoken words given the speech history.In recent years, many speech recognition systems have been developed that use language models created for specific languages. And the use of language models in speech recognition serves to increase the efficiency of speech recognition. Many researchers have developed a traditional language model for the Uzbek language [8] –[12], but this model does not give the expected results. This requires the construction of other models for the Uzbek language. This article provides information about natural language, building natural language models, and applying them to speech recognition. Discusses research related to the construction of natural language models, problems that arise in the construction of statistical models, and approaches that can be used to solve them.
{"title":"Construction of Language Models for Uzbek Language","authors":"N. Mamatov, N. Niyozmatova, A. Samijonov, B. Samijonov","doi":"10.1109/ICISCT55600.2022.10146788","DOIUrl":"https://doi.org/10.1109/ICISCT55600.2022.10146788","url":null,"abstract":"A language model is a set of restrictions on the sequence of words allowed in a given language, and these restrictions can be expressed, for example, by the rules of a generative grammar or by a statistic of each pair of words evaluated in a given language. simple educational building. Although there are words with similar-sounding phonemes, it is usually not difficult for people to recognize the word. It mostly has to do with knowing the context and being very good at what words or phrases might be in it. The purpose of the language model is to provide context to the speech recognition system. The language model determines what words are allowed in the system language and in what order they can occur.Language models are trained, i.e., n-gram probabilities are estimated by observing sequences of words in a text corpus. Confusion reduction is typically performed on training data containing millions of word tokens. But, as has been observed, reducing confusion does not improve speech recognition results. Therefore, algorithms should be used that improve language models in terms of their impact on speech recognition, especially language models that determine the probability distribution of the speaker’s next spoken words given the speech history.In recent years, many speech recognition systems have been developed that use language models created for specific languages. And the use of language models in speech recognition serves to increase the efficiency of speech recognition. Many researchers have developed a traditional language model for the Uzbek language [8] –[12], but this model does not give the expected results. This requires the construction of other models for the Uzbek language. This article provides information about natural language, building natural language models, and applying them to speech recognition. Discusses research related to the construction of natural language models, problems that arise in the construction of statistical models, and approaches that can be used to solve them.","PeriodicalId":332984,"journal":{"name":"2022 International Conference on Information Science and Communications Technologies (ICISCT)","volume":"513 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123072680","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 : 2022-09-28DOI: 10.1109/ICISCT55600.2022.10146913
Tingyu Guo, Boping Tian
Option pricing is an important topic in the field of quantitative finance. The traditional Black-Scholes model formulation requires a large number of assumptions, which often does not exist in practice, and the statistically-based regression analysis and time series methods have poor fitting ability for non-stationary data. Deep learning has advantages over traditional econometric models in identifying the structure and patterns of data, and can effectively learn the nonlinear and non-stationary characteristics of time series, which is more suitable for the study of option pricing problems. The Transformer model has greater advantages over the traditional recurrent neural network model in the processing of time series data, mainly in terms of performance and speed. In this work, we will compare different models and get the deep learning model with the strongest prediction ability. Based on the collected data related to 50 ETF options and stocks in the Chinese market for empirical analysis, it is demonstrated that the Transformer model outperforms the traditional deep learning model in time series prediction.
{"title":"The Study of Option Pricing Problems based on Transformer Model","authors":"Tingyu Guo, Boping Tian","doi":"10.1109/ICISCT55600.2022.10146913","DOIUrl":"https://doi.org/10.1109/ICISCT55600.2022.10146913","url":null,"abstract":"Option pricing is an important topic in the field of quantitative finance. The traditional Black-Scholes model formulation requires a large number of assumptions, which often does not exist in practice, and the statistically-based regression analysis and time series methods have poor fitting ability for non-stationary data. Deep learning has advantages over traditional econometric models in identifying the structure and patterns of data, and can effectively learn the nonlinear and non-stationary characteristics of time series, which is more suitable for the study of option pricing problems. The Transformer model has greater advantages over the traditional recurrent neural network model in the processing of time series data, mainly in terms of performance and speed. In this work, we will compare different models and get the deep learning model with the strongest prediction ability. Based on the collected data related to 50 ETF options and stocks in the Chinese market for empirical analysis, it is demonstrated that the Transformer model outperforms the traditional deep learning model in time series prediction.","PeriodicalId":332984,"journal":{"name":"2022 International Conference on Information Science and Communications Technologies (ICISCT)","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125111976","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 : 2022-09-28DOI: 10.1109/ICISCT55600.2022.10146791
Mahmudur Rahman, Ceren Dilsiz, M. Ordu
Polymer optical fibers have great significance due to a wide range of applications, such as data transmission, sensing, and illumination. In this study, we proposed a novel hollow-core polymer optical fiber fabricated by a commercially available 3D printer with guiding properties in the near-infrared region. The fiber was drawn conventionally using a thermal drawing tower from a 3D printed preform. Light guidance by inhibited coupling through the air core surrounded with six-pointed star cladding tubes was demonstrated. Two significant transmission bands with low losses of 0.325 dB/cm at 1300 nm and 0.38 dB/cm at 1530 nm were detected.
{"title":"3D printed hollow-core polymer optical fiber with six-pointed star cladding for the light guidance in the near-IR regime","authors":"Mahmudur Rahman, Ceren Dilsiz, M. Ordu","doi":"10.1109/ICISCT55600.2022.10146791","DOIUrl":"https://doi.org/10.1109/ICISCT55600.2022.10146791","url":null,"abstract":"Polymer optical fibers have great significance due to a wide range of applications, such as data transmission, sensing, and illumination. In this study, we proposed a novel hollow-core polymer optical fiber fabricated by a commercially available 3D printer with guiding properties in the near-infrared region. The fiber was drawn conventionally using a thermal drawing tower from a 3D printed preform. Light guidance by inhibited coupling through the air core surrounded with six-pointed star cladding tubes was demonstrated. Two significant transmission bands with low losses of 0.325 dB/cm at 1300 nm and 0.38 dB/cm at 1530 nm were detected.","PeriodicalId":332984,"journal":{"name":"2022 International Conference on Information Science and Communications Technologies (ICISCT)","volume":"221 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122453798","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 : 2022-09-28DOI: 10.1109/ICISCT55600.2022.10146766
Komoliddin Tashmetov, M. Aliev, R. Aliev
The article discusses the development of artificial intelligence in railway transport and its areas of application. One of the elements of automation and telemechanic, jointless rail circuits with current pickup, was investigated and, based on the knowledge base function, was used to create expert systems. A mathematical model has been developed to determine one of the operating modes of a jointless rail circuit with current pickup. A simulation model has been developed, a methodology for applying artificial intelligence has been investigated in relation to the storage of knowledge, semantics, frames and formal logic. Algorithms and programs have been developed for the creation of expert systems for these models, as well as their advantages and disadvantages.
{"title":"Mathematical model and algorithms for research and diagnostics of the track control sensor to create an expert system","authors":"Komoliddin Tashmetov, M. Aliev, R. Aliev","doi":"10.1109/ICISCT55600.2022.10146766","DOIUrl":"https://doi.org/10.1109/ICISCT55600.2022.10146766","url":null,"abstract":"The article discusses the development of artificial intelligence in railway transport and its areas of application. One of the elements of automation and telemechanic, jointless rail circuits with current pickup, was investigated and, based on the knowledge base function, was used to create expert systems. A mathematical model has been developed to determine one of the operating modes of a jointless rail circuit with current pickup. A simulation model has been developed, a methodology for applying artificial intelligence has been investigated in relation to the storage of knowledge, semantics, frames and formal logic. Algorithms and programs have been developed for the creation of expert systems for these models, as well as their advantages and disadvantages.","PeriodicalId":332984,"journal":{"name":"2022 International Conference on Information Science and Communications Technologies (ICISCT)","volume":"119 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122470262","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 : 2022-09-28DOI: 10.1109/ICISCT55600.2022.10146785
Javlon Tursunov, Gulrukh Memonova
Cotton production is considered crucial in various parts of the world and determining the diseases well in advance is a vital factor that directly has an effect on the yield. To tackle this issue, a CNN - based approach has been proposed which can detect a diseased plant and the leaf. For detection, the VGG19 artificial neural network has been trained by using google collaboratory. Moreover, unsupervised learning was used with Kaggle cotton plant dataset for training the model followed by validation and testing. Once the training is done, the saved model can easily predict whether the plant or leaf is diseased or not.
{"title":"Detection of Cotton Plant Disease Using CNN","authors":"Javlon Tursunov, Gulrukh Memonova","doi":"10.1109/ICISCT55600.2022.10146785","DOIUrl":"https://doi.org/10.1109/ICISCT55600.2022.10146785","url":null,"abstract":"Cotton production is considered crucial in various parts of the world and determining the diseases well in advance is a vital factor that directly has an effect on the yield. To tackle this issue, a CNN - based approach has been proposed which can detect a diseased plant and the leaf. For detection, the VGG19 artificial neural network has been trained by using google collaboratory. Moreover, unsupervised learning was used with Kaggle cotton plant dataset for training the model followed by validation and testing. Once the training is done, the saved model can easily predict whether the plant or leaf is diseased or not.","PeriodicalId":332984,"journal":{"name":"2022 International Conference on Information Science and Communications Technologies (ICISCT)","volume":"478 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121973562","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 : 2022-09-28DOI: 10.1109/ICISCT55600.2022.10147014
Orzikul Shukurov, Bobir Shirinov
In article, the detection of above pounce upon supported on collections Mining undergrounds was studied, including the detection of pounce upon using a clandestine Markov model, detection of pounce upon using theorem networks, detection of pounce upon using bunch methods, detection of pounce upon using the facilitate agent method, detection of pounce upon using neuronal networks, detection of pounce upon using transmissible algorithms, detection of pounce upon using fleecy scientific reasoning rules. The pointers of tone-beginning detection in indefinite studies are precondition in the table.
{"title":"Network Attack Detection Based on Data Mining Methods","authors":"Orzikul Shukurov, Bobir Shirinov","doi":"10.1109/ICISCT55600.2022.10147014","DOIUrl":"https://doi.org/10.1109/ICISCT55600.2022.10147014","url":null,"abstract":"In article, the detection of above pounce upon supported on collections Mining undergrounds was studied, including the detection of pounce upon using a clandestine Markov model, detection of pounce upon using theorem networks, detection of pounce upon using bunch methods, detection of pounce upon using the facilitate agent method, detection of pounce upon using neuronal networks, detection of pounce upon using transmissible algorithms, detection of pounce upon using fleecy scientific reasoning rules. The pointers of tone-beginning detection in indefinite studies are precondition in the table.","PeriodicalId":332984,"journal":{"name":"2022 International Conference on Information Science and Communications Technologies (ICISCT)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122112213","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 : 2022-09-28DOI: 10.1109/ICISCT55600.2022.10147001
A. Turgunov
It is known that the study and research of existing problems of medicine using modern information technologies is the most relevant today. Mathematical modeling of the activities of the regulatory mechanisms of living systems at the organismal, organ, cellular and molecular-genetic levels is one of the promising areas in the field of medical biology. The scientific research discusses the results of a quantitative study of the regulatory mechanisms of liver cells and hepatitis B viruses based on mathematical and computer models by using the Matlab application package. The study of the quasi-stationary state of the liver cell under the pressure of hepatitis B viruses using mathematical modeling methods is one of the urgent tasks. The use of mathematical modeling to analyze the interaction of the regulatory mechanisms of molecular genetic systems of liver cells and hepatitis B viruses makes it possible to analyze the main forms of infectious viral hepatitis B in a quasi-stationary state of liver cells. The results of a qualitative study of the equations of hepatitis B regulators in the quasi-stationary state of liver cells are presented.
{"title":"Application of mathematical modeling methods and use of information technologies for research of viral hepatitis B","authors":"A. Turgunov","doi":"10.1109/ICISCT55600.2022.10147001","DOIUrl":"https://doi.org/10.1109/ICISCT55600.2022.10147001","url":null,"abstract":"It is known that the study and research of existing problems of medicine using modern information technologies is the most relevant today. Mathematical modeling of the activities of the regulatory mechanisms of living systems at the organismal, organ, cellular and molecular-genetic levels is one of the promising areas in the field of medical biology. The scientific research discusses the results of a quantitative study of the regulatory mechanisms of liver cells and hepatitis B viruses based on mathematical and computer models by using the Matlab application package. The study of the quasi-stationary state of the liver cell under the pressure of hepatitis B viruses using mathematical modeling methods is one of the urgent tasks. The use of mathematical modeling to analyze the interaction of the regulatory mechanisms of molecular genetic systems of liver cells and hepatitis B viruses makes it possible to analyze the main forms of infectious viral hepatitis B in a quasi-stationary state of liver cells. The results of a qualitative study of the equations of hepatitis B regulators in the quasi-stationary state of liver cells are presented.","PeriodicalId":332984,"journal":{"name":"2022 International Conference on Information Science and Communications Technologies (ICISCT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128697556","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 : 2022-09-28DOI: 10.1109/ICISCT55600.2022.10146928
D. Saidov, Musulmon Yakhshiboevich Lolaev, Shamsiddin Ramazonov
The problem of forming a latent feature space through nonlinear transformations of different type features is considered. Two types of transformations are used: the replacement of gradations of nominal features by the values of the function of objects belonging to classes and the combination of features according to the rules of hierarchical agglomerative grouping. The dimension of the new latent space is less than the original one and it is determined by the grouping algorithm. The ordering of latent features in relation to informativeness allows solving the problem of the curse of dimensionality and visualizing data taking into account the description of class objects.A comparative analysis of linear and nonlinear methods for reducing the dimension of space is given. The division of methods using the division of objects into classes and without such division is given. Without division into classes, the PCA and T-SNE methods are implemented on data in interval measurement scales.Using the method of calculating generalized estimates of the objects it is doing their visualization according to a certain set of different type features.
{"title":"Nonlinear transformations of different type features and the choice of latent space based on them","authors":"D. Saidov, Musulmon Yakhshiboevich Lolaev, Shamsiddin Ramazonov","doi":"10.1109/ICISCT55600.2022.10146928","DOIUrl":"https://doi.org/10.1109/ICISCT55600.2022.10146928","url":null,"abstract":"The problem of forming a latent feature space through nonlinear transformations of different type features is considered. Two types of transformations are used: the replacement of gradations of nominal features by the values of the function of objects belonging to classes and the combination of features according to the rules of hierarchical agglomerative grouping. The dimension of the new latent space is less than the original one and it is determined by the grouping algorithm. The ordering of latent features in relation to informativeness allows solving the problem of the curse of dimensionality and visualizing data taking into account the description of class objects.A comparative analysis of linear and nonlinear methods for reducing the dimension of space is given. The division of methods using the division of objects into classes and without such division is given. Without division into classes, the PCA and T-SNE methods are implemented on data in interval measurement scales.Using the method of calculating generalized estimates of the objects it is doing their visualization according to a certain set of different type features.","PeriodicalId":332984,"journal":{"name":"2022 International Conference on Information Science and Communications Technologies (ICISCT)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114197695","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 : 2022-09-28DOI: 10.1109/ICISCT55600.2022.10146996
O. Porubay, I. Siddikov, Khasanova Madina
The paper considers the issues of optimizing the modes of electric power systems based on the methods of intelligent technologies: evolutionary and ant algorithms, taking into account the features of the object under consideration. An optimization criterion has been formulated, which includes minimizing the total cost of fuel in electric power facilities. The main restrictions imposed by the dynamics of the functioning of technological units and their mode of operation are determined. These restrictions are presented in the form of a system of linear equations that characterize the steady state of the units, as well as in the form of inequalities, which are the limiting restrictions on the parameters of the generated electricity. To solve this problem, evolutionary modeling algorithms and an ant colony algorithm have been developed. A comparative analysis of these algorithms was carried out in order to determine their capabilities and scope. The use of evolutionary algorithms in problems with discrete values of variables does not require any assumptions and simplifications of the problem. When solving the problem of optimal placement and determination of the parameters of compensating devices and linear regulators, it was possible to reduce losses in the system by 3.5%.
{"title":"Algorithm for optimizing the mode of electric power systems by active power","authors":"O. Porubay, I. Siddikov, Khasanova Madina","doi":"10.1109/ICISCT55600.2022.10146996","DOIUrl":"https://doi.org/10.1109/ICISCT55600.2022.10146996","url":null,"abstract":"The paper considers the issues of optimizing the modes of electric power systems based on the methods of intelligent technologies: evolutionary and ant algorithms, taking into account the features of the object under consideration. An optimization criterion has been formulated, which includes minimizing the total cost of fuel in electric power facilities. The main restrictions imposed by the dynamics of the functioning of technological units and their mode of operation are determined. These restrictions are presented in the form of a system of linear equations that characterize the steady state of the units, as well as in the form of inequalities, which are the limiting restrictions on the parameters of the generated electricity. To solve this problem, evolutionary modeling algorithms and an ant colony algorithm have been developed. A comparative analysis of these algorithms was carried out in order to determine their capabilities and scope. The use of evolutionary algorithms in problems with discrete values of variables does not require any assumptions and simplifications of the problem. When solving the problem of optimal placement and determination of the parameters of compensating devices and linear regulators, it was possible to reduce losses in the system by 3.5%.","PeriodicalId":332984,"journal":{"name":"2022 International Conference on Information Science and Communications Technologies (ICISCT)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114877940","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 : 2022-09-28DOI: 10.1109/ICISCT55600.2022.10146920
F. Nuraliev, S. Safarov, M. Artikbayev, Abdirozikov O.Sh
In the article a mathematical model based on the Hamilton-Ostrogradsky variational principle is presented. Using the Kirkhgoff-Lyav hypothesis, the mathematical model in three-dimensional form is transformed into a two-dimensional model. The variational representation of potential and kinetic energy as well as the variation of work done by external forces, Cauchy relations, Hooke’s law, and Lorentz force and Maxwell’s electromagnetic forces are determined using the tensor view. In this case, the effects of the electromagnetic field on the deformation stress state of the magnetoelastic plate are considered. The result was a mathematical model in the form of a system of high-order differential equations with special derivatives with initial and boundary conditions relative to the displacement. To solve the problem, a computational algorithm was developed, for which a practical software tool was created, computational experiments were conducted, and the results obtained were analyzed.
{"title":"Calculation Results of the Task of Geometric Nonlinear Deformation of Electro-magneto-elastic Thin Plates in a Complex Configuration","authors":"F. Nuraliev, S. Safarov, M. Artikbayev, Abdirozikov O.Sh","doi":"10.1109/ICISCT55600.2022.10146920","DOIUrl":"https://doi.org/10.1109/ICISCT55600.2022.10146920","url":null,"abstract":"In the article a mathematical model based on the Hamilton-Ostrogradsky variational principle is presented. Using the Kirkhgoff-Lyav hypothesis, the mathematical model in three-dimensional form is transformed into a two-dimensional model. The variational representation of potential and kinetic energy as well as the variation of work done by external forces, Cauchy relations, Hooke’s law, and Lorentz force and Maxwell’s electromagnetic forces are determined using the tensor view. In this case, the effects of the electromagnetic field on the deformation stress state of the magnetoelastic plate are considered. The result was a mathematical model in the form of a system of high-order differential equations with special derivatives with initial and boundary conditions relative to the displacement. To solve the problem, a computational algorithm was developed, for which a practical software tool was created, computational experiments were conducted, and the results obtained were analyzed.","PeriodicalId":332984,"journal":{"name":"2022 International Conference on Information Science and Communications Technologies (ICISCT)","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126242305","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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