Plant Disease Forecasting Based on Wavelet Transformation and Support Vector Machine
Journal Title: International Journal of Research in Agricultural Sciences - Year 2018, Vol 5, Issue 2
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.
Authors and Affiliations
Hong Wang, et al.
Keywords
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