DocumentCode :
3470919
Title :
An intuitive view to compare intelligent systems
Author :
Nazemi, A.R. ; Akbarzadeh, M.R.T. ; Hosseini, S.M.
Author_Institution :
Dept. of Civil Eng., Ferdowsi Univ. of Mashhad, Iran
Volume :
2
fYear :
2004
fDate :
27-30 June 2004
Firstpage :
566
Abstract :
In this study, one of the most complicated problems in water resources engineering, i.e., rainfall-runoff modeling is introduced and nine soft computing-based modeling approaches are considered to describe the rainfall-runoff process in a particular case study. For each of these nine approaches, many modeling choices are evaluated and the best modeling choice is selected by an intuitive two-stage competition among all modeling choices for a particular modeling approach. This competition is then applied among the best modeling choice of applied approaches and the best one is highlighted. The results shows that the modeling efficiency increases by moving toward neural modeling; particularly, the fuzzy clustering-based neural network is the most efficient and accurate paradigm among performed systems for modeling rainfall-runoff process in the considered case study. In addition, for interpreting the results, a new concept, i.e., intelligence space, and its consequent definitions are introduced that can be used as a general framework for comparing intelligent systems.
Keywords :
fuzzy neural nets; rain; water resources; fuzzy clustering; intelligent systems; neural network; rainfall-runoff process; water resources engineering; Civil engineering; Competitive intelligence; Computational intelligence; Decision making; Intelligent systems; Neural networks; Phase measurement; Power system modeling; Rivers; Water resources;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Fuzzy Information, 2004. Processing NAFIPS '04. IEEE Annual Meeting of the
Print_ISBN :
0-7803-8376-1
Type :
conf
DOI :
10.1109/NAFIPS.2004.1337363
Filename :
1337363
Link To Document :
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