Application of bionic models for situation management; CEUR Workshop Proceedings; Vol. 2763 : Computing in Physics and Technology 2020 (CPT2020)
| Parent link: | CEUR Workshop Proceedings: Online Proceedings for Scientific Conferences and Workshops Vol. 2763 : Computing in Physics and Technology 2020 (CPT2020).— 2020.— [5 p.] |
|---|---|
| المؤلف الرئيسي: | |
| مؤلفون مشاركون: | , |
| مؤلفون آخرون: | |
| الملخص: | Title screen he article discusses the concept of choosing the sequence of control actions in order to minimize the possibility of the system statetransition to an adverse one. For this purpose, the bionic model based on the synthesis of information approach, neural networks anda genetic algorithm is developed. The functionality of each of the model elements and their interaction are presented in this paper.Special attention is paid to neuroevolutionary interaction. At the same time, information about control actions is encapsulated in thegene, which allowed increasing the functionality of the algorithm due to multidimensional data representation. The article describesthe principle of data representation in bionic models, which differs from the existing ones by the possibility of explicit or implicitrepresentation of the control action in the chromosome. In the explicit representation one neural network is formed, it describes theeffect of any of the control actions involved in the training. An implicit view creates a set of models, each of which describes the effectof only one control action. A brief description of the software implemented in the Python programming language is provided. |
| اللغة: | الإنجليزية |
| منشور في: |
2020
|
| سلاسل: | Plenary Session |
| الموضوعات: | |
| الوصول للمادة أونلاين: | http://ceur-ws.org/Vol-2763/CPT2020_paper_p-2.pdf |
| التنسيق: | MixedMaterials الكتروني فصل الكتاب |
| KOHA link: | https://koha.lib.tpu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=663076 |
MARC
| LEADER | 00000naa0a2200000 4500 | ||
|---|---|---|---|
| 001 | 663076 | ||
| 005 | 20251127095854.0 | ||
| 035 | |a (RuTPU)RU\TPU\network\34245 | ||
| 035 | |a RU\TPU\network\34151 | ||
| 090 | |a 663076 | ||
| 100 | |a 20210122d2020 k||y0engy50 ba | ||
| 101 | 0 | |a eng | |
| 102 | |a DE | ||
| 135 | |a drcn ---uucaa | ||
| 181 | 0 | |a i | |
| 182 | 0 | |a b | |
| 200 | 1 | |a Application of bionic models for situation management |f O. M. Gerget, N. A. Markova | |
| 203 | |a Text |c electronic | ||
| 225 | 1 | |a Plenary Session | |
| 300 | |a Title screen | ||
| 320 | |a [References: 16 tit.] | ||
| 330 | |a he article discusses the concept of choosing the sequence of control actions in order to minimize the possibility of the system statetransition to an adverse one. For this purpose, the bionic model based on the synthesis of information approach, neural networks anda genetic algorithm is developed. The functionality of each of the model elements and their interaction are presented in this paper.Special attention is paid to neuroevolutionary interaction. At the same time, information about control actions is encapsulated in thegene, which allowed increasing the functionality of the algorithm due to multidimensional data representation. The article describesthe principle of data representation in bionic models, which differs from the existing ones by the possibility of explicit or implicitrepresentation of the control action in the chromosome. In the explicit representation one neural network is formed, it describes theeffect of any of the control actions involved in the training. An implicit view creates a set of models, each of which describes the effectof only one control action. A brief description of the software implemented in the Python programming language is provided. | ||
| 461 | |t CEUR Workshop Proceedings |o Online Proceedings for Scientific Conferences and Workshops | ||
| 463 | |t Vol. 2763 : Computing in Physics and Technology 2020 (CPT2020) |o Proceedings of the 8th International Scientific Conference, Moscow region, Russia, November 09-13, 2020 |v [5 p.] |d 2020 | ||
| 610 | 1 | |a электронный ресурс | |
| 610 | 1 | |a труды учёных ТПУ | |
| 610 | 1 | |a information approach | |
| 610 | 1 | |a neural networks | |
| 610 | 1 | |a genetic algorithm | |
| 610 | 1 | |a bionic model | |
| 610 | 1 | |a choice of control actions | |
| 610 | 1 | |a нейронные сети | |
| 610 | 1 | |a бионические методы | |
| 700 | 1 | |a Gerget |b O. M. |c Specialist in the field of informatics and computer technology |c Professor of Tomsk Polytechnic University, Doctor of Sciences |f 1974- |g Olga Mikhailovna |3 (RuTPU)RU\TPU\pers\31430 |9 15593 | |
| 701 | 1 | |a Markova |b N. A. |c linguist |c Lecturer of Tomsk Polytechnic University |f 1976- |g Natalia Aleksandrovna |3 (RuTPU)RU\TPU\pers\32853 |9 16701 | |
| 712 | 0 | 2 | |a Национальный исследовательский Томский политехнический университет |b Инженерная школа информационных технологий и робототехники |b Отделение автоматизации и робототехники |3 (RuTPU)RU\TPU\col\23553 |
| 712 | 0 | 2 | |a Национальный исследовательский Томский политехнический университет |b Школа базовой инженерной подготовки |b Отделение иностранных языков |3 (RuTPU)RU\TPU\col\23510 |
| 801 | 2 | |a RU |b 63413507 |c 20210122 |g RCR | |
| 856 | 4 | |u http://ceur-ws.org/Vol-2763/CPT2020_paper_p-2.pdf | |
| 942 | |c CF | ||