Performance of Fuzzy Inference System for Calorific Value Predicting by Using The Mamdani Method

Abstract

It is well known that the energy content of fuel is characterized by its calorific value which is usually measured by using a bomb calorimeter. In many analysis, the calorific value is usually related with the proximate analysis results. In this study, the calorific value predicting program based on the proximate analysis data using the fuzzy inference system with Mamdani method has been developed. In our analysis, the proximate analysis data of moisture and volatile matter contents are used as input and the calorific value as output. The results showed that the influence of the moisture content is more dominant in determining the calorific value of fuel than volatile matter content. The performance of the calorific value predicting program also shown that the prediction error is about 0.75% to 5.2%. The obtained calorific value is well reproduced the experimental data.