NDLI: Prediction and Early Warning Method for Flea Beetle Based on Semi-supervised Learning Algorithm

Content Provider	IEEE Xplore Digital Library
Author	Ting Li Jingfeng Yang Xiaoqin Peng Zhimin Chen Chengyang Luo
Copyright Year	2008
Description	Author affiliation: South China Agric. Univ., Guangzhou (Jingfeng Yang; Zhimin Chen) \|\| Tianfu Coll., Southwestern Univ. of Finance & Econ., Mianyang (Xiaoqin Peng) \|\| Chung Tak Lighting Control Syst. (Guangzhou) Ltd., Guangzhou (Chengyang Luo) \|\| Zhongshan Torch Polytech., Zhongshan (Ting Li)
Abstract	The prediction and early warning for vegetable crop diseases and insect pests commonly based on expertspsila knowledge of plant protection while math modeling methods are used to analyze the associated data quantitatively scarcely. This paper takes advantage of labeled historical data to extract association rules as the supervised information, and combining with the use of the unsupervised learning method iterative self- organizing data analysis techniques algorithm (ISODATA) to establish the model semi-supervised learning algorithm for predicting and early warning vegetable pest flea beetle. Semi-supervised learning algorithm not only obtains a high accuracy of supervised learning method, but also takes advantage of the flexibility of unsupervised learning method, which is significative for both research and practice. The experimental results of Guangdong vegetable pest flea beetle show the prediction and early warning accuracy of semi-supervised learning method provides a higher accuracy rate than that of k-mean clustering, support vector machine and RBF neural network in the same condition.
Starting Page	217
Ending Page	221
File Size	373470
Page Count	5
File Format	PDF
ISBN	9780769533049
DOI	10.1109/ICNC.2008.371
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-10-18
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Data analysis Crops Predictive models Association Rules Data mining ISODATA Unsupervised learning Diseases Semi-supervised Learning Prediction and Early Warning Insects Flea Beetle Semisupervised learning Iterative algorithms Protection
Content Type	Text
Resource Type	Article

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