Hybrid Expert System for Wheat Diseases Diagnosis Using Fuzzy Logic, Neural Network and Bayesian Method

Authors

  • Wijdan R. Abdulhussien

DOI:

https://doi.org/10.32792/utq/utjsci/v5i2.126

Keywords:

Wheat Disease Diagnosis, Fuzzy Logic, Neural Network, Bayesian Methods.

Abstract

Expert system is a branch of Artificial Intelligence is a collection of programs which has the ability to reason,
justify and answer the queries in a particular domain as a human expert would do. It can be applied to various fields. This research was designed hybrid expert system for the diseases diagnosis of wheat rust by incorporating application of fuzzy logic, neural networks and Bayesian method. The research aim is to tackling the control and remedial measures for disease management for the wheat diseases. The expert system is intended to help the farmers, researchers and students and provides an efficient goal-oriented approach for solving common problems of wheat rust. The system gives results that are correct and consistent.

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Published

2015-05-01

Issue

Section

Articles

How to Cite

Hybrid Expert System for Wheat Diseases Diagnosis Using Fuzzy Logic, Neural Network and Bayesian Method . (2015). University of Thi-Qar Journal of Science, 5(2), 80-88. https://doi.org/10.32792/utq/utjsci/v5i2.126