DocumentCode :
3315320
Title :
On The Application of Fuzzy Regression Trees in Modeling the Efficiency of a Power Station
Author :
Crockett, Keeley ; Bandar, Zuhair ; O´Shea, James ; Al-Attar, Sammi
Author_Institution :
Manchester Metropolitan Univ., Manchester
fYear :
2007
fDate :
23-26 July 2007
Firstpage :
1
Lastpage :
6
Abstract :
Typically regression trees are not capable of generating a continuous output as a function of inputs and are not suitable for modeling process control problems. Fuzzy logic controllers offer an alternative approach to modeling such process efficiently but often rely on human experts to articulate a set of rules. The generation of fuzzy rules by experts is difficult and based on the subjective perception of individuals. This paper presents a novel approach to modeling process control applications using fuzzy regression trees. Two sets of experiments were designed and conducted. The first involved measuring the output gradient of the fuzzy regression tree to investigate the applicability of fuzzy regression trees in modelling process control applications. The second assessed the efficiency of the fuzzy model produced. The results have shown that an effective fuzzy model can be produced and as a consequence a considerable improvement in the performance can be achieved.
Keywords :
fuzzy control; neural nets; power engineering computing; power station control; regression analysis; artificial neural network; fuzzy logic controller; fuzzy regression tree; fuzzy rule; power station; Fuzzy control; Fuzzy logic; Humans; Industrial control; Mathematical model; Power generation; Power generation economics; Power system modeling; Process control; Regression tree analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Fuzzy Systems Conference, 2007. FUZZ-IEEE 2007. IEEE International
Conference_Location :
London
ISSN :
1098-7584
Print_ISBN :
1-4244-1209-9
Electronic_ISBN :
1098-7584
Type :
conf
DOI :
10.1109/FUZZY.2007.4295346
Filename :
4295346
Link To Document :
بازگشت