Modified Support Vector Machine and Animal Migration based Citrus Disease Recognition for Precision Farming

Authors

  • Mrs. S. Lingeswari, Dr. P. M. Gomathi

DOI:

https://doi.org/10.17762/msea.v71i4.1111

Abstract

Citrus disease prediction plays the biggest role in the agricultural farm environment where differentiation of citrus disease from the black spots, scrub on fruits are more challenging. In the study that has been done up to now, this result is accomplished by presenting the multi-class SVM based citrus disease prediction system. However existing work tends to have followed issues: In top hat filter, with the presence of non-ground objects finding variation will be more difficult. Weighted segmentation requires more computational complexity. Hybridized feature selection cannot ensure the accurate selection outcome where features that satisfies all these parameters cannot be selected well. Multi class support vector machine is utilized to perform classification which requires supervised labels for ensuring the accurate classification rate. This problem is addressed in the study work that has been presented by the implementation of the approach known as Modified Support Vector Machine based Citrus Disease Recognition Framework (MSVM-CDRF). In the proposed work pre-processing is done using Improved Top Hat Filter. Here gradient is utilized to find the intensity elevation change between neighbouring pixels. Feature weighted fuzzy clustering method is introduced to ensure the accurate segmentation outcome. Here multi objective optimization methodology is presented to provide for the best function choices. To guarantee the best feature selection based on PCA score, entropy, and skewness-based covariance vector, an animal migrating method is used. A revised Support Vector Machine built on deep learning is developed to forecast citrus diseases. The MATLAB simulation environment is used for the whole study of the research project, and it has been shown that the suggested technique produces better outcomes than the current solution.

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Published

2022-10-18

How to Cite

Mrs. S. Lingeswari, Dr. P. M. Gomathi. (2022). Modified Support Vector Machine and Animal Migration based Citrus Disease Recognition for Precision Farming. Mathematical Statistician and Engineering Applications, 71(4), 5180–5196. https://doi.org/10.17762/msea.v71i4.1111

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Section

Articles