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《Journal of Yangtze University(Natural Science Edition)Agricultural Science Volume》 2008-03
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Pest Prediction Research Based on Combining Factor Analysis and Neural Network

JIA Wei-kuan,WANG Hui (College of Plant Protection,Shandong Agricultural University,Taian,Shandong 271018,China)DING Shi-fei,SU Chun-yang School of Computer Science and Technology,China University of Mining andTechnology,Xuzhou,Jiangsu 221008,China  
The appearance of pest is a nonlinear system.There are many predicting factors that influence the appearance of pest.They are interrelated to some extent.When using neural network to predict,it is not propitious for the design and computation.combined the principle of factor analysis and neural network and builds the model basing on the combination of factor analysis and neural network were built.By factor analysis the dimensionality of predicting factors was reduced,and the data after dimension reduction was regarded as the input of the network,then the predicting results after training.By analyzing the second period prediction of Helicoverpa armigera(Hübner) of Yuncheng,Shandong,it is proved that the prediction inaccuracy of the new model is not reduced,the convergence velocity speed up,and the error of prediction value is reduced.It shows that this model has wide application prospects in the aspects of the prediction of plant diseases and insect pests.
【Fund】: 国家自然科学基金项目(40574001);; 中国科学院智能信息处理重点实验室开放基金项目(IIP2006-2)
【CateGory Index】: S433
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