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Agricultural Information Service Quality Evaluation Algorithm Based on Genetic Algorithm, BP Neural Network and Multiple Regressions

文献类型： 外文期刊

作者： Chen, Cheng 1 ; Wu, Huarui 1 ;

作者机构： 1.Beijing Acad Agr & Forestry Sci, Beijing Res Ctr Informat Technol Agr, Beijing 100097, Peoples R China

关键词： agricultural information service;quality evaluation algorithm;BP neural network;multiple regressions;genetic algorithms

期刊名称：ADVANCES IN MECHATRONICS AND CONTROL ENGINEERING II, PTS 1-3

ISSN： 1660-9336

年卷期： 2013 年 433-435 卷

页码：

收录情况： SCI

摘要： Information service objects in agriculture relatively have a complex demand due to agricultural regional and seasonal. The construction of information service quality evaluation model contributes to analyze the influencing factors that influence the quality of information service, proving guidance for agricultural information service. Combined with genetic Algorithm, BP neural network and multiple regression, a hybrid BP network based on the integration of BP Network and multiple regression models is proposed, and the initial weights of hybrid BP network is optimized by hybrid genetic algorithm, effectively avoid the flaws when these methods used separately. Proved by the experiment, information service quality evaluation model constructed by a hybrid BP network based on the optimization of genetic Algorithm has a good accuracy and generalization ability, the mean error within 5%.

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