[1]冯冬青,郭艳..遗传算法改进BP神经网络在地下水水质评价中的应用[J].郑州大学学报(工学版),2009,30(03):126-129.[doi:10.3969/j.issn.1671-6833.2009.03.032]
　Feng Dongqing,Guo Yan.Genetic algorithm improves the application of BP neural network in groundwater quality assessment[J].Journal of Zhengzhou University (Engineering Science),2009,30(03):126-129.[doi:10.3969/j.issn.1671-6833.2009.03.032]
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遗传算法改进BP神经网络在地下水水质评价中的应用()
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《郑州大学学报(工学版)》[ISSN:1671-6833/CN:41-1339/T]

卷:
30卷
期数:
2009年03期
页码:
126-129
栏目:
出版日期:
1900-01-01

文章信息/Info

Title:
Genetic algorithm improves the application of BP neural network in groundwater quality assessment

作者:
冯冬青; 郭艳.
郑州大学电气工程学院,河南,郑州,450001, 郑州大学电气工程学院,河南,郑州,450001
Author(s):
Feng Dongqing; Guo Yan
关键词:
BP神经网络;  遗传算法;  水质评价
Keywords:
DOI:
10.3969/j.issn.1671-6833.2009.03.032
文献标志码:
A
摘要:
为了准确、高效地评定地下水水质,提出了一种遗传算法与神经网络相结合的混合评价算法,针对水质评价的多变量和非线性,采用BP神经网络对其进行综合评价计算,BP算法易陷入局部极小的缺点则通过引入遗传算法来克服,将两者有机的结合起来实现神经网络的训练和知识库的建立.通过算法比较和实例结果分析,证明了该算法的有效性.
Abstract:

In order to accurately and efficiently assess groundwater quality, a hybrid evaluation algorithm combining genetic algorithm and neural network is proposed, aiming at the multivariate and nonlinear water quality evaluation, BP neural network is used to comprehensively evaluate and calculate, BP algorithm is easy to fall into local minimity, but the introduction of genetic algorithm to overcome it, the two are organically combined to realize the training of neural network and the establishment of knowledge base. The effectiveness of the algorithm is proved by algorithm comparison and case result analysis.

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更新日期/Last Update: 1900-01-01