Plant Disease Forecasting Based on Wavelet Transformation and Support Vector Machine

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Year:
2018
Type of Publication:
Article
Keywords:
Plant Disease Prediction, Environment Information, Wavelet Transformation, SVM
Authors:
Wang, Hong; Zhang, Shanwen; Shao, Yu; Zhang, Yunlong
Journal:
IJRAS
Volume:
5
Number:
2
Pages:
90-94
Month:
March
ISSN:
2348-3997
Abstract:
A forecasting method of plant disease based on wavelet transformation (WT) and Support Vector Machine (SVM) is introduced. The environment information data is essentially an unstationary time sequence, which can be decomposed into different frequency channels by WT and obtain the forecasting features. The disease can be forecasted by SVM. The average forecasting precision was over 86%. Experimental results on three common kinds of cucumber diseases show that the proposed method is more effective for plant disease forecasting
Full text: IJRAS_659_Final.pdf

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