A Fuzzy Interface System for the Prediction of Caffeine Addiction

Abstract

Caffeine is a stimulant which enables the prevention or delay of drowsiness or a feeling of sleepiness. Caffeine is an unregulated substance in most parts of the world and hence poses a threat of addiction. The symptoms of caffeine addiction and withdrawal are defined well but are large in number and sometimes inseparable from the same symptoms of other conditions. Fuzzy logic can be used to combine many such symptoms and arrive at a certain conclusion. This paper aims to implement fuzzy logic to predict the risk caffeine addiction in functioning adults based on certain predictors. The system takes into account four such predictors. The proposed model gives adequate results with an accuracy of eighty to hundred percent under different scenarios.