Pub Date : 1900-01-01DOI: 10.4018/978-1-7998-1581-5.ch004
V. Gorbachenko, K. Savenkov
Digital twins are widely used in modern industry. A digital twin is a computer model that copies the behavior of a physical object. Digital twins of objects with distributed parameters are mathematically boundary value problems for partial differential equation. Traditionally, such problems are solved by finite difference and finite element methods, which require a complex grid construction procedure. The numerical solution of boundary value problems employs mesh less methods that do not require grid construction. Among mesh fewer methods, projection methods that use radial basis functions (RBFs) as basic functions are popular. Methods using RBF allow us to obtain a differentiable solution at any point in the solution domain, applicable to problems of arbitrary dimension with complex computational domains. When solving the problem, the parameters of the basic functions are selected, and the weights are calculated so that the residuals obtained after the substitution of the approximate solution at the test points in the equation are zero.
{"title":"Improving Algorithms for Learning Radial Basic Functions Networks to Solve the Boundary Value Problems","authors":"V. Gorbachenko, K. Savenkov","doi":"10.4018/978-1-7998-1581-5.ch004","DOIUrl":"https://doi.org/10.4018/978-1-7998-1581-5.ch004","url":null,"abstract":"Digital twins are widely used in modern industry. A digital twin is a computer model that copies the behavior of a physical object. Digital twins of objects with distributed parameters are mathematically boundary value problems for partial differential equation. Traditionally, such problems are solved by finite difference and finite element methods, which require a complex grid construction procedure. The numerical solution of boundary value problems employs mesh less methods that do not require grid construction. Among mesh fewer methods, projection methods that use radial basis functions (RBFs) as basic functions are popular. Methods using RBF allow us to obtain a differentiable solution at any point in the solution domain, applicable to problems of arbitrary dimension with complex computational domains. When solving the problem, the parameters of the basic functions are selected, and the weights are calculated so that the residuals obtained after the substitution of the approximate solution at the test points in the equation are zero.","PeriodicalId":265693,"journal":{"name":"Avatar-Based Control, Estimation, Communications, and Development of Neuron Multi-Functional Technology Platforms","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128089163","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 : 1900-01-01DOI: 10.4018/978-1-7998-1581-5.ch007
A. Tuskov, A. Goldina, O. Luzgina, O. Salnikova
One of the determining factors for ensuring regional food security is the sectoral structure of production. It determines the specialization and combination of industries, on which the degree of tension, balance, and economic efficiency of the production program of peasant farming depends. This is achieved subject to the proportionality of the elements of the sectoral complex. For this, it is necessary to coordinate production volumes with available resources, the level of intensification of crop production and animal husbandry, the size of crops, individual crops, and livestock, etc. The size of peasant farms and their structure (the composition and area of land, the combination and size of main and additional industries, the structure of crops) depend on many natural and economic factors. There are various options for the organization of production and territory for the same farming with certain resources of land, labor, and capital. The main task is to choose the optimal one that corresponds to the interests of the farmer and gives the maximum economic effect.
{"title":"Optimizing the Production Parameters of Peasant Holdings for Industrial Development in the Digitalization Era","authors":"A. Tuskov, A. Goldina, O. Luzgina, O. Salnikova","doi":"10.4018/978-1-7998-1581-5.ch007","DOIUrl":"https://doi.org/10.4018/978-1-7998-1581-5.ch007","url":null,"abstract":"One of the determining factors for ensuring regional food security is the sectoral structure of production. It determines the specialization and combination of industries, on which the degree of tension, balance, and economic efficiency of the production program of peasant farming depends. This is achieved subject to the proportionality of the elements of the sectoral complex. For this, it is necessary to coordinate production volumes with available resources, the level of intensification of crop production and animal husbandry, the size of crops, individual crops, and livestock, etc. The size of peasant farms and their structure (the composition and area of land, the combination and size of main and additional industries, the structure of crops) depend on many natural and economic factors. There are various options for the organization of production and territory for the same farming with certain resources of land, labor, and capital. The main task is to choose the optimal one that corresponds to the interests of the farmer and gives the maximum economic effect.","PeriodicalId":265693,"journal":{"name":"Avatar-Based Control, Estimation, Communications, and Development of Neuron Multi-Functional Technology Platforms","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122261175","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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