DocumentCode
2910327
Title
Tuning fuzzy systems by simulated annealing to predict time series with added noise
Author
Almaraashi, Majid ; John, Robert
Author_Institution
Centre for Comput. Intell., De Montfort Univ., Leicester, UK
fYear
2010
fDate
8-10 Sept. 2010
Firstpage
1
Lastpage
5
Abstract
In this paper, a combination of fuzzy system models and simulated annealing are used to predict Mackey-Glass time series with different levels of added noise 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 under singleton and non-singleton fuzzifications for both Mamdani and Takagi-Sugeno (TSK). The results of the proposed methods are compared by their ability to handle uncertainty.
Keywords
fuzzy logic; simulated annealing; time series; Mackey-Glass time series; Mamdani fuzzy system; Takagi-Sugeno fuzzy system; fuzzy system tuning; nonsingleton fuzzification; simulated annealing; singleton fuzzification; Fuzzy sets; Fuzzy systems; Markov processes; Noise; Simulated annealing; Time series analysis; Uncertainty;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Intelligence (UKCI), 2010 UK Workshop on
Conference_Location
Colchester
Print_ISBN
978-1-4244-8774-5
Electronic_ISBN
978-1-4244-8773-8
Type
conf
DOI
10.1109/UKCI.2010.5625596
Filename
5625596
Link To Document