[1]赵建明 姚念民.基于网络结构进化解决逻辑运算问题[J].计算机技术与发展,2010,(09):86-89.
　ZHAO Jian-ming,YAO Nian-min.Solving Logical Computing Problems Based on Neural Network Evolution[J].,2010,(09):86-89.
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基于网络结构进化解决逻辑运算问题()
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
期数:
2010年09期
页码:
86-89
栏目:
智能、算法、系统工程
出版日期:
1900-01-01

文章信息/Info

Title:
Solving Logical Computing Problems Based on Neural Network Evolution
文章编号:
1673-629X（2010）09-0086-04
作者:
赵建明1 姚念民2
[1]福建师范大学福清分校[2]哈尔滨工程大学
Author(s):
ZHAO Jian-ming; YAO Nian-min
[1]Fuqing Branch of Fujian Normal University[2]Harbin Engineering University
关键词:
遗传算法; 自进化; 网络结构
Keywords:
genetic algorithm;  self-evolution;  network structure
分类号:
TP183
文献标志码:
A
摘要:
遗传算法在复杂问题的优化搜索方面具有很好的健壮性和性能。文中模拟自然界的进化过程,试图使用遗传算法搜索适当的解决问题的神经元网络结构。通过构造一个自进化系统,从单个神经元个体构成的初始群体出发,模拟自然界中个体的学习、变异、繁殖,演示系统中群体的自进化过程,找出解决逻辑运算问题的适当的神经元网络结构。实验结果表明,与标准的BP网络比较,使用遗传算法的自进化系统能够找到解决逻辑运算问题更优的网络结构
Abstract:
Genetic algorithm can effectively solve many complex problems through optimized searching.This paper tried to search the proper neural network structure which could solve the problem by simulating the evolution process of nature using genetic algorithm.Through building a self-evolution system,the proper structure of the neural network that can accomplish logical computations may be found by beginning with a single neuron and then self-evolution.The experimental results indicate that genetic algorithm can help finding a better structure of neural networks than only standard BP network

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备注/Memo

备注/Memo:
高效能服务器和存储技术国家重点实验室开放基金项目（2009HSSA08）赵建明（1976-），男，福建福清人。硕士，讲师，研究方向为网络与优化；姚念民，博士，教授，研究方向为网络存储安全与优化
更新日期/Last Update: 1900-01-01