Title :
Fuzzy modeling by ID3 algorithm and its application to prediction of heater outlet temperature
Author :
Tani, Tomoyuki ; Sakoda, Woto ; Tanaka, Kazuo
Abstract :
The authors propose a practical method for fuzzy modeling. The ID3 algorithm, used in the field of machine learning, was applied to select the effective variables in the premises of a fuzzy model and compute their boundary values. Even when the process had many variables, effective variables were chosen and their boundary values for fuzzification were computed automatically. This method was applied to a system to predict heater outlet temperature. Good results were obtained, and the system was operated with the required accuracy without adding new rules or without modifying rules
Keywords :
fuzzy logic; fuzzy set theory; learning (artificial intelligence); learning systems; temperature control; ID3 algorithm; boundary values; fuzzy logic; fuzzy modeling; fuzzy set theory; heater outlet temperature prediction; machine learning; Fuzzy sets; Fuzzy systems; Heat engines; Information technology; Input variables; Machine learning; Machine learning algorithms; Mechanical systems; Piecewise linear techniques; Predictive models; Systems engineering and theory; Temperature;
Conference_Titel :
Fuzzy Systems, 1992., IEEE International Conference on
Conference_Location :
San Diego, CA
Print_ISBN :
0-7803-0236-2
DOI :
10.1109/FUZZY.1992.258780