| 基于改进遗传算法的RBF网络的截球策略 |
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| 引用本文： | 廖本先,杨宜民,项凡. 基于改进遗传算法的RBF网络的截球策略[J]. 控制工程, 2009, 0(Z2) |
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| 作者姓名： | 廖本先 杨宜民 项凡 |
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| 作者单位： | 广东工业大学自动化学院; |
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| 摘 要： | 在RoboCup2D仿真足球比赛中,球员的底层动作设计的好坏直接影响着比赛的输赢,特别是一些关键的动作,比如截球、传球、射门等动作。鉴于此,提出一种新的截球方法,即改进的遗传算法和RBF神经网络相结合的截球方法。该方法是用改进的遗传算法优化RBF神经网络的结构参数,通过优化,提高了网络的全局搜索效率。实验表明,经过改进遗传算法优化的RBF神经网络的截球成功率比单一的RBF神经网络截球成功率高很多。
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| 关 键 词： | 截球 RBF神经网络 遗传算法 RoboCup |
Intercepting Ball Strategy of Improved Genetic Algorithm and RBF Network |
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| LIAO Ben-xian,YANG Yi-min,XIANG Fan. Intercepting Ball Strategy of Improved Genetic Algorithm and RBF Network[J]. Control Engineering of China, 2009, 0(Z2) |
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| Authors: | LIAO Ben-xian YANG Yi-min XIANG Fan |
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| Affiliation: | Faculty of Automation;Guangdong University Of Technology;Guangzhou 510090;China |
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| Abstract: | In the RoboCup2D simulation soccer game,the design of the player bottom action is very important and it directly impacts on winning or losing the game,especially some fundamental action,such as intercepting ball,passing ball,shooting ball.In view of the fact,based on the improved genetic algorithm and RBF neural network in intercepting ball,a new method of intercepting ball is proposed.Namely,the improved genetic algorithm is to optimize the structure parameter of RBF neural network.It enhances the network ... |
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| Keywords: | intercepting ball RBF neural network genetic algorithm RoboCup |
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