Plant Disease Forecasting Based on Wavelet Transformation and Support Vector Machine

Hits: 6254
Select Volume / Issue:
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
Note:
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. CC BY-NC-SA 4.0 Creative Commons License: https://creativecommons.org/licenses/by-nc-sa/4.0/
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

Our Journals

IJECCE
International Journal of Electronics Communication and Computer Engineering
ISSN(Online): 2249 - 071X
ISSN (Print) : 2278 – 4209
www.ijecce.org
Submissions open
IJAIR
International Journal of Agriculture Innovations and Research ISSN(Online) : 2319 – 1473
www.ijair.org
Submissions open
IJISM
International Journal of Innovation in Science and Mathematics
ISSN : 2347 – 9051
www.ijism.org
Submissions open
IJEIR
International Journal of Engineering Innovations and Research
ISSN(Online) : 2277 – 5668
www.ijeir.org
Submissions are open.

IJAIM
International Journal of Artificial Intelligence and Mechatronics ISSN(Online) : 2320 – 5121
www.ijaim.org
Submissions open
IJRAS
International Journal of Research in Agricultural Sciences ISSN(Online) : 2348 – 3997
www.ijras.org
Submissions open