Open AccessCalorific value predicting based on moisture and volatile matter contents using fuzzy inference system
Author(s) -
V I Variani
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1825/1/012006
Subject(s) - heat of combustion , fuzzy inference system , moisture , water content , fuzzy inference , fuzzy logic , adaptive neuro fuzzy inference system , mathematics , value (mathematics) , inference system , environmental science , inference , fuzzy control system , statistics , computer science , artificial intelligence , combustion , chemistry , meteorology , engineering , physics , geotechnical engineering , organic chemistry
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 %.