An RNA evolutionary algorithm based on gradient descent for function optimization

The optimization of numerical functions with multiple independent variables was a significant challenge with numerous practical applications in process control systems, data fitting, and engineering designs. Although RNA genetic algorithms offer clear benefits in function optimization, including rap...

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Vydané v:	Journal of computational design and engineering Ročník 11; číslo 4; s. 332 - 357
Hlavní autori:	Wu, Qiuxuan, Zhao, Zikai, Chen, Mingming, Chi, Xiaoni, Zhang, Botao, Wang, Jian, Zhilenkov, Anton A, Chepinskiy, Sergey A
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Oxford Oxford University Press 01.08.2024 한국CDE학회
Predmet:	Adaptive algorithms Dung Evolutionary algorithms Genetic algorithms Heuristic methods Independent variables Mutation Operators (mathematics) Optimization Optimization algorithms Process controls Ribonucleic acid RNA 기계공학 RNA-inspired operations heuristic algorithm function optimization adaptive gradient descent mutation operator
ISSN:	2288-5048, 2288-4300, 2288-5048
On-line prístup:	Získať plný text
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