Calorific value predicting based on moisture and volatile matter contents using fuzzy inference system

Abstract

The calorific value is one of the most important characteristics of fuel and it determines the energy content of fuel. In this study, we developed the calorific value predicting program based on proximate analysis of moisture and volatile matter contents using the fuzzy inference system with Tsukamoto method. The moisture and volatile matter contents are used as input and the caloric value as an output. Every fuzzy variable is divided into two linguistic values of fuzzy set i.e. low and high. By evaluation on fuzzy inference rules output, it is found that moisture content has more dominant influence on the calorific value. We also found that the calorific value predicting program has prediction error of about 0 to 1.80 %.