Temperature Prediction System in Kanyakumari District using Higher Order Stochastic Fuzzy Logic Model

Abstract

Forecasting the weather is one of the most difficult tasks for meteorological services worldwide. Temperature is the most important weather factor affecting people and crops. Fuzzy logic has two main parts: a knowledge base and fuzzy reasoning. In this study, a Higher Order Stochastic Fuzzy Logic model was created and used to analyze temperature data from Kanyakumari. The model's steps included fuzzification, a stochastic process, and defuzzification. The predicted outputs were compared with actual temperature data to check the model's performance.