| Форма представления | Статьи в зарубежных журналах и сборниках |
| Год публикации | 2019 |
| Язык | английский |
|
Мокшин Анатолий Васильевич, автор
|
| Библиографическое описание на языке оригинала |
Mokshin A. V. Adaptive genetic algorithms used to analyze behavior of complex system / A. V. Mokshin, V. V. Mokshin, L. M. Sharnin // Communications in Nonlinear Science and Numerical Simulation. - 2019. - Vol. 71. - P. 174-186. |
| Аннотация |
In the present study, we consider a complex system whose behavior is characterized by set of various time-dependent factors. Some of these factors can characterize the external influences on the system, whereas other factors contain information generated by system. We demonstrate that time-dependence of these factors can be reproduced by the nonlinear regression model. The concrete form of this regression model is constructed on the basis of the genetic algorithms technique. This allows us to predict a possible behavior of the system and to identify the so-called significant factors that have a significant impact on the behavior of the system. To demonstrate validity of the method, we apply it to analyze the data characterizing a manufacturing company and the meteorological data. |
| Ключевые слова |
complex system, regression analysis, machine-learning, genetic algorithms |
| Название журнала |
Communications in Nonlinear Science and Numerical Simulation
|
| URL |
https://doi.org/10.1016/j.cnsns.2018.11.014 |
| Пожалуйста, используйте этот идентификатор, чтобы цитировать или ссылаться на эту карточку |
https://repository.kpfu.ru/?p_id=189849 |
Полная запись метаданных  |
| Поле DC |
Значение |
Язык |
| dc.contributor.author |
Мокшин Анатолий Васильевич |
ru_RU |
| dc.date.accessioned |
2019-01-01T00:00:00Z |
ru_RU |
| dc.date.available |
2019-01-01T00:00:00Z |
ru_RU |
| dc.date.issued |
2019 |
ru_RU |
| dc.identifier.citation |
Mokshin A. V. Adaptive genetic algorithms used to analyze behavior of complex system / A. V. Mokshin, V. V. Mokshin, L. M. Sharnin // Communications in Nonlinear Science and Numerical Simulation. - 2019. - Vol. 71. - P. 174-186. |
ru_RU |
| dc.identifier.uri |
https://repository.kpfu.ru/?p_id=189849 |
ru_RU |
| dc.description.abstract |
Communications in Nonlinear Science and Numerical Simulation |
ru_RU |
| dc.description.abstract |
In the present study, we consider a complex system whose behavior is characterized by set of various time-dependent factors. Some of these factors can characterize the external influences on the system, whereas other factors contain information generated by system. We demonstrate that time-dependence of these factors can be reproduced by the nonlinear regression model. The concrete form of this regression model is constructed on the basis of the genetic algorithms technique. This allows us to predict a possible behavior of the system and to identify the so-called significant factors that have a significant impact on the behavior of the system. To demonstrate validity of the method, we apply it to analyze the data characterizing a manufacturing company and the meteorological data. |
ru_RU |
| dc.language.iso |
ru |
ru_RU |
| dc.subject |
complex system |
ru_RU |
| dc.subject |
regression analysis |
ru_RU |
| dc.subject |
machine-learning |
ru_RU |
| dc.subject |
genetic algorithms |
ru_RU |
| dc.title |
Adaptive genetic algorithms used to analyze behavior of complex system |
ru_RU |
| dc.type |
Статьи в зарубежных журналах и сборниках |
ru_RU |
|
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