Temperature Forecasting System Using Fuzzy Mathematical Model

Abstract

Temperature study and model development related to estimation is an essential and important task not only for a human life but also for animal life, agriculture, tourism, water reservation and evaporation, and many other fields. Regression is considered a dominant prediction model which is heavily used in forecasting in spite of the difficulties related to the number of available measurements, the order of the model and the nonlinearity of the data. In this article, the purpose is to use a nonlinear model structure to forecast the temperature at the airport of Mumbai city in India using the fuzzy logic technique. The datasets were collected for twelve months period starting from 1st of January 2009 to 31st of December at a weather underground in India. The datasets were divided into two parts, 288 days (80%) of the data for training and the remaining 72 days (20%) for testing. The results obtained and the error calculated using the fuzzy logic model were satisfactory.