Model Building with Neural Networks Based on Genetic Algorithms for Structure-activity Relationships of Pesticide

Abstract

Abstract: In this paper, a neural network based on genetic algorithms was proposed for a QSAR model building of herbicidal N-(1-methyl-1-phenylethyl)phenylacetamides. Since neural networks can express complicated structure-activity relationships, and the combination of Genetic Algorithms can help the networks to jump out of the local optimal points, thus, it's peeds up the covergence of the training. At the same time, it's prediction precision has been notably raised.

Key words: Genetic algorithms, Neural networks, Herbicide, QSAR, Model building

CLC Number:

O639

TrendMD:

SUN Wei-Guo, CHEN De-Zhao, CHEN Ya-Qiu, HU Shang-Xu . Model Building with Neural Networks Based on Genetic Algorithms for Structure-activity Relationships of Pesticide[J]. Chem. J. Chinese Universities, 1998, 19(6): 871.

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Model Building with Neural Networks Based on Genetic Algorithms for Structure-activity Relationships of Pesticide

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