A neural networks for real coded genetic algorithm

被引：0
|
作者：
Gong, DX [1 ]
Ruan, XG [1 ]
机构：
[1] Beijing Univ Technol, Coll Elect Informat & Control Engn, Beijing 100022, Peoples R China
来源：
2003 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS, INTELLIGENT SYSTEMS AND SIGNAL PROCESSING, VOLS 1 AND 2, PROCEEDINGS | 2003年
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper proposed an idea and presented a scheme of using Neural Network to implement real coded Genetic Algorithm (GA). The Arithmetical Crossover is generated to its' multiple parent version and the Random Mutation operator is also generated to its' multiple mutation point version, two artificial neuron models are also designed for the two genetic operations. We validate our scheme with some benchmark functions. The significance of our research means that the GA can be implemented with hardware and the inherent parallelism of GA can be explicitly realized, as a result, the real-time performance of GA will be remarkably improved, and the application field of GA will be widely broadened.
引用
收藏
页码：874 / 879
页数：6
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