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《Journal of Anhui Agricultural Sciences》 2008-25
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Study on the Early Warning Model of Phyllotreta striolata Based on the Maximum Likelihood Integration

LI Ting et al (Zhongshan Torch Vocational College,Zhongshan,Guangdong 528436)  
The early warning model of Phyllotreta striolata in vegetables was set up by using the maximum likelihood model.Aiming at the disadvantage of the maximum likelihood that more training samples were needed for accurate prediction generally,its integration algorithm that could enhance the generalization ability of the learning system significantly was put forward.The maximum likelihood integration algorithm reduced the quantity demands of the training samples.The data of the test on P.striolata in vegetables in Guangdong Province,the accuracy rate of early warning by the maximum likelihood integration algorithm was higher than that by nearest-neighbor algorithm,k-mean clustering and support vector machine.
【Fund】: 华南农业大学校长基金项目(2007K017)
【CateGory Index】: TP18
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