ABSTRACT: The motivation for this research is to adopt fuzzy logic for the groupings of a categorization model which will be used to detect cassava plant infection based on a group of dependent factors observed from various parts of cassava plants. Based on review of related works surrounding cassava plant infection detection, some factors that are related with the identification were identified and validated by experienced Botanists. Trilateral membership functions were formulated using the input and output variables via fuzzification. The rule base model was put together using IF-THEN statements to combine the values of the inputs with their respective output values. The MATLAB Fuzzy.....
Key wards: fuzzy logic, cassava plant, plant diseases, fuzzification, fuzzy logic model, categorization, MATLAB, rule base.
[1]. Alexander, G.L., Warren, J.M., Andras, T., Allison, S., Andrea, D., Carlos, A.R., Denice, S.F., Melinda, T. and Joseph, A.C. (2007).Mobile Phone-Based Remote Patient Monitoring System for Management of Hypertension in Diabetic 25: 1 - 12.
[2]. Bhatta, N. and Jyoti, K. (2012). A Novel Approach for Still-birth Diagnosis using Data Mining and Fuzzy Logic. 16 - 21.
[3]. Djam, X.Y. and Kimbi, Y.H. (2011).Fuzzy Expert System for the Management of Hypertension.
[4]. Imianvan, A.A. and Obi, J.C. (2012).Cognitive Neuro-Fuzzy Expert System for Hypotension Control.Computer Engineering and Intelligent Systems 3(6): 21 - 31.
[5]. Khormehr, A. and Maihami, V. (2016). A Novel Fuzzy Expert System Design for Predicting Still-birth. 138(4): 33 - 38.