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» On the design of metaheuristic algorithms using fuzzy rules
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EAAI
2006
161views more  EAAI 2006»
14 years 9 months ago
Genetic learning and performance evaluation of interval type-2 fuzzy logic controllers
Type-2 fuzzy sets, which are characterized by membership functions (MFs) that are themselves fuzzy, have been attracting interest. This paper focuses on advancing the understandin...
Dongrui Wu, Woei Wan Tan
CIMCA
2005
IEEE
14 years 11 months ago
Fuzzy System Modeling with the Genetic and Differential Evolutionary Optimization
This paper compares the performance of two provably successful evolutionary optimization tools in the optimization of a Fuzzy-Rule-Base (FRB) for the three well known fuzzy modeli...
Mehmet Bodur, Adnan Acan, Talip Akyol
GECCO
2006
Springer
253views Optimization» more  GECCO 2006»
15 years 1 months ago
A novel approach to optimize clone refactoring activity
Achieving a high quality and cost-effective tests is a major concern for software buyers and sellers. Using tools and integrating techniques to carry out low cost testing are chal...
Salah Bouktif, Giuliano Antoniol, Ettore Merlo, Ma...
JCP
2008
124views more  JCP 2008»
14 years 9 months ago
Novel Fuzzy Logic Controllers with Self-Tuning Capability
Two controllers which extend the PD+I fuzzy logic controller to deal with the plant having time varying nonlinear dynamics are proposed. The adaptation ability of the first self tu...
Fong Chwee Teng, Ahmad Lotfi, Ah Chung Tsoi
EUSFLAT
2009
156views Fuzzy Logic» more  EUSFLAT 2009»
14 years 7 months ago
Interactive Fuzzy Modeling by Evolutionary Multiobjective Optimization with User Preference
One of the new trends in genetic fuzzy systems (GFS) is the use of evolutionary multiobjective optimization (EMO) algorithms. This is because EMO algorithms can easily handle two c...
Yusuke Nojima, Hisao Ishibuchi