Design and Analysis of Fuzzy Times Series Forecasting Model for Thermal Power Generation

The fuzzy time series has recently received increasing attention because of its capability of dealing with vague and incomplete data. There have been a variety of models developed to either improve forecasting accuracy or reduce computation overhead. It has been applied to forecast various fields and have been shown to forecast better than other models. Hence, this paper we have to apply fuzzy time series forecasting on thermal power generation data set during the period of 1995-2011. The empirical results show that numerically as well as graphically.