DocumentCode :
1979015
Title :
Fuzzy systems as a fusion framework for describing nonlinear flow in porous media
Author :
Nazemi, A.-R. ; Akbarzadeh-T, M.-R. ; Hosseini, S.M.
Author_Institution :
Dept. of Civil Eng., Ferdowsi Univ. of Mashhad, Iran
fYear :
2003
fDate :
24-26 July 2003
Firstpage :
389
Lastpage :
394
Abstract :
By increasing the velocity of flow in coarse grain materials, local turbulences are often imposed to the flow. As a result, the flow regime through rockfill structures deviates from linear Darcy law; and nonlinear or non-Darcy flow equations will be applicable. Even though the structures of these nonlinear equations have some physical justifications, they still need empirical studies to estimate parameters of these equations. Hence there is a great deal of uncertainty as an inherent part of the estimation process. In this paper we investigate fuzzy systems paradigm to combine three of the most commonly validated and utilized empirical solutions in the current literature. In this way, the results of the three empirical equations serve as inputs, and the combination framework serve as fusion algorithm. The results show that when learning injected to fuzzy logic based models, the system provides a powerful solution with a strong ability to track reality. Specifically, this paper concludes that ANFIS provide accurate combination framework with greatest performance among the considered conventional alternatives as well as Mamdani structures.
Keywords :
adaptive systems; flow through porous media; fuzzy logic; fuzzy neural nets; fuzzy systems; nonlinear equations; ANFIS; Mamdani structure; adaptive neuro-fuzzy inference system; combination framework; estimation process; flow velocity; fusion algorithm; fusion framework; fuzzy logic based model; fuzzy system; grain material; linear Darcy law; non-Darcy flow equation; nonlinear flow equation; porous media; rockfill structure; Availability; Building materials; Civil engineering; Fuzzy logic; Fuzzy systems; Nonlinear equations; Parameter estimation; Power system modeling; Shape; Uncertainty;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Fuzzy Information Processing Society, 2003. NAFIPS 2003. 22nd International Conference of the North American
Print_ISBN :
0-7803-7918-7
Type :
conf
DOI :
10.1109/NAFIPS.2003.1226816
Filename :
1226816
Link To Document :
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