Multi-objective aero acoustic optimization of rear end in a simplified car model by using hybrid Robust Parameter Design, Artificial Neural Networks and Genetic Algorithm methods

2014 ◽  
Vol 90 ◽  
pp. 123-132 ◽  
Author(s):  
Sajjad Beigmoradi ◽  
Hassan Hajabdollahi ◽  
Asghar Ramezani
Keyword(s):  
Genetic Algorithm ◽  
Neural Networks ◽  
Artificial Neural Networks ◽  
Parameter Design ◽  
Robust Parameter Design ◽  
Multi Objective ◽  
Car Model ◽  
Robust Parameter ◽  
Artificial Neural

MATHEMATICAL SUPPORT FOR INDUCTION SOLDERING CONTROL BASED ON INTELLIGENT METHODS OF INFORMATION PROCESSING

2021 ◽  
pp. 81-87
Author(s):  
А.В. Милов
Keyword(s):  
Genetic Algorithm ◽  
Neural Networks ◽  
Artificial Neural Networks ◽  
Information Processing ◽  
Mathematical Models ◽  
Technological Process ◽  
Artificial Neural ◽  
Intelligent Methods

В статье представлены математические модели на основе искусственных нейронных сетей, используемые для управления индукционной пайкой. Обучение искусственных нейронных сетей производилось с использованием многокритериального генетического алгоритма FFGA. This article presents mathematical models based on artificial neural networks used to control induction soldering. The artificial neural networks were trained using the FFGA multicriteria genetic algorithm. The developed models allow to control induction soldering under conditions of incomplete or unreliable information, as well as under conditions of complete absence of information about the technological process.

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