Recursive learning of genetic algorithms with task decomposition and varied rule set | |
Fang, Lei; Guan, Sheng-Uei; Zhang, Haofan | |
关键词 | Algorithmic framework Classification accuracy Conventional approach Generalization accuracy Genetic algorithm (GAs) Pre-mature convergences Real-world problem Task decomposition |
出处 | Modeling Applications and Theoretical Innovations in Interdisciplinary Evolutionary Computation |
内容类型 | 图书章节 |
URI标识 | http://www.corc.org.cn/handle/1471x/3311356 |
专题 | 西安交通大学 |
推荐引用方式 GB/T 7714 | Fang, Lei,Guan, Sheng-Uei,Zhang, Haofan. Recursive learning of genetic algorithms with task decomposition and varied rule set[Ch]. Modeling Applications and Theoretical Innovations in Interdisciplinary Evolutionary Computation, |
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