The Application on the Forecast of Plant Disease Based on an Improved BP Neural Network

被引：1

作者：

Jin, Baoshi ^{[1
,2
]}

Zuo, Yuhu ^{[1
]}

Ma, Xiaodan ^{[3
]}

Guan, Haiou ^{[3
]}

Tan, Feng ^{[3
]}

机构：

[1] Heilongjiang Bayi Agr Univ, Coll Agron, Daqing, Peoples R China

[2] Heilongjiang Land Reclamat Bureau, Harbin, Peoples R China

[3] Heilongjiang Bay, Coll Informat Technol, DaQing, Peoples R China

来源：

MATERIALS SCIENCE AND INFORMATION TECHNOLOGY, PTS 1-8 | 2012年 / 433-440卷

关键词：

BP neural network; Parameter Learning; Plant Diseases; Forecast;

D O I：

10.4028/www.scientific.net/AMR.433-440.5469

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

Aiming at the disadvantages of large computing, slow convergence and easily trapping into local minima of traditional BP network, a new method named batch momentum learning algorithm which combining the momentum with batch gradient descent algorithm has been used to be as the learning algorithm of connection weights and threshold of BP neural network, through using this method to forecast the prevalence of plant disease, the convergence speed of BP neural network has been enhanced.

引用

页码：5469 / +

页数：2

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