Implementation of A Fuzzy Logic Progression For Alcohol Addicts Using Fuzzy Control System(FCS)
Ogbolu Melvin Omone, Eric Aggrey, Márta Takács, Miklós Kozlovszky · 2020
The use of the Reduced Alcohol Intake (RAI) logic model is to help monitor alcoholic addicts and help them reduce alcohol intake for a better life and improved academic performance. The purpose of this study is to use the Mamdani Fuzzy Inference System (MFIS) component, which includes the application of a T-S (Takagi-Sugeno) model-based Fuzzy Control System (FCS) and a Fuzzy Logic System (FLS) as a rule-based system (Fuzzy Control System - FCS) to assemble all inputs in the RAI model to achieve classified fuzzy outputs. As initiated in the theoretical logic model (the RAI logic model), there is a direct identification of breakpoints for a transition between phases in the model. Thus, it can be used as an AI system that is efficient to monitor and examine the progression of alcohol addicts (to know what percentage of improvement they have reached overtime). Using the T-S method, the core parameters (motivation and self-determined state) of the RAI model were analyzed to find a linear interaction between the existing variables. In this paper, the variables of motivation and self-determined state are scaled between 0 to 10 to predict the level of improvement in percentage (%).