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Time Series Forecasting Using a TSK Fuzzy System tuned with Simulated Annealing
Almaraashi, Majid; John, Robert; Coupland, Simon et al.
2010In 2010 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2010)
Peer reviewed
 

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Abstract :
[en] In this paper, a combination of a Takagi-Sugeno fuzzy system (TSK) and simulated annealing is used to predict well known time series by searching for the best configuration of the fuzzy system. Simulated annealing is used to optimise the parameters of the antecedent and the consequent parts of the fuzzy system rules. The results of the proposed method are encouraging indicating that simulated annealing and fuzzy logic are able to combine well in time series prediction.
Disciplines :
Computer science
Electrical & electronics engineering
Author, co-author :
Almaraashi, Majid;  De Montfort Univ, Ctr Computat Intelligence, Fac Technol, Leicester LE1 9BH, Leics, England.
John, Robert;  De Montfort Univ, Ctr Computat Intelligence, Fac Technol, Leicester LE1 9BH, Leics, England.
Coupland, Simon;  De Montfort Univ, Ctr Computat Intelligence, Fac Technol, Leicester LE1 9BH, Leics, England.
Hopgood, Adrian ;  Université de Liège > HEC - Ecole de gestion de l'ULG : Direction générale
Language :
English
Title :
Time Series Forecasting Using a TSK Fuzzy System tuned with Simulated Annealing
Publication date :
2010
Event name :
2010 IEEE World Congress on Computational Intelligence
Event organizer :
IEEE, IEEE Computat Intelligence Soc, Int Neural Network Soc, Evolut Program Soc, IET
Event place :
Barcelona, Spain
Event date :
JUL 18-23, 2010
Audience :
International
Main work title :
2010 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2010)
Publisher :
IEEE
ISBN/EAN :
978-1-4244-6919-2
Peer reviewed :
Peer reviewed
Commentary :
978-1-4244-6920-8
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