Сибирский федеральный университет

Тип публикации: статья из журнала

Год издания: 2015

Идентификатор DOI: 10.3103/S1060992X15020083

Ключевые слова: Fuzzy logic, Global optimization, Multi-agent systems, Neural networks, Particle swarm optimization, Swarm intelligence, Artificial intelligence, Fuzzy control, Fuzzy inference, Fuzzy neural networks, Intelligent agents, Multi agent systems, Reinforcement, Stochastic systems, Computer experiment, Computer methods, Global optimization method, Modification methods, Neurofuzzy control, Test functions, Weighted averages, Particle swarm optimization (PSO)

Аннотация: The new modification method of the particle swarm optimization (PSO) is presented. Intensified adaptation properties of this stochastic computer method are based on the hybridization it with the weighted average coordinates method and reinforcement swarm intelligence via the neuro fuzzy control of the agent particles behavior. The results of computer experiments of the global optimization on the test functions of 2, 50, 100 variables with multiple extremes are presented. © Allerton Press, Inc., 2015.

Журнал: Optical Memory and Neural Networks (Information Optics)

Выпуск журнала: Vol. 24, Is. 2

Номера страниц: 102-108

• Koshur V.D. (Institute of Space and Information Technology of the Siberian Federal University, Krasnoyarsk, Russian Federation)

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