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ISSN 1004-9037
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Edited by: Editorial Board of Journal of Data Acquisition and Processing
P.O. Box 2704, Beijing 100190, P.R. China
Sponsored by: Institute of Computing Technology, CAS & China Computer Federation
Undertaken by: Institute of Computing Technology, CAS
Published by: SCIENCE PRESS, BEIJING, CHINA
Distributed by:
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      07 April 2023, Volume 38 Issue 2   
    Article

    OPTIMIZED SVM MODEL FOR MAIZE AND RICE LEAF DISEASE DETECTION
    K.K.Nivethithaa, Dr.S.Vijayalakshmi
    Journal of Data Acquisition and Processing, 2023, 38 (2): 3146-3159 . 

    Abstract

    Crop disease is not only treated for Food Security(FS) globally. However, it also leads to tragic consequences for farmers whose livelihood depends on healthy crops and food production. Agricultural exports must take various procedures to prevent crop health and crop loss due to disease. Plant disease detection is a significant factor in crop loss prevention. Recently, mobile-based plant disease detection approaches are getting popularity among formers. Still, this application has some limitations in other plant disease detection (PDD) due to the poor performance of the adopted present PDD methods. This study has addressed these issues by considering only two PDD such as rice and maize disease. It introduces a fish swarm-optimized Support Vector Machine(FSOSVM) model to perform the PDD. The food hunting behaviour of the fish swarm optimizer(FSO) is used to fine-tune the SVM parameters to improve detection accuracy.

    Keyword

    Data Mining,Crop disease, Fish swarm optimizer, Machine learning, leaf disease, SVM, Optimization, Classification.


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ISSN 1004-9037

         

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