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Fuzzy genetic algorithms

There are a few approaches in which fuzzy set theory and evolutionary algorithms become highly interactive parmers. They mostly concern the following alternatives.  [Pg.285]

Fuzzy Encoding and Fuzzy Set Operations in Genetic Algoritms [Pg.285]

New developments which have still to be checked for their usability in data evaluation of depth profiles are artificial neural networks [2.16, 2.21-2.25], fuzzy clustering [2.26, 2.27] and genetic algorithms [2.28]. [Pg.21]

Sutton, R. and Marsden, G.D. (1997) A Fuzzy Autopilot Optimized using a Genetic Algorithm, Journal of Navigation, 50(1), pp. 120-131. [Pg.432]

Chang CL, Lo SL, Yu SL (2005) Applying fuzzy theory and genetic algorithm to interpolate precipitation. J Hydrol 314 92-104... [Pg.146]

Cheng CT, Ou CP, Chau KW (2002) Combining a fuzzy optimal model with a genetic algorithm to solve multi-objective rainfall-runoff model calibration. J Hydrol 268 72-86... [Pg.146]

Moraga, C. Meyer zu Bexten, E. 1997. Fuzzy Knowledge-Based Genetic Algorithms. Information Sciences, Vol. 103, pp. 101-114. [Pg.129]

Thus, multilinear models were introduced, and then a wide series of tools, such as nonlinear models, including artificial neural networks, fuzzy logic, Bayesian models, and expert systems. A number of reviews deal with the different techniques [4-6]. Mathematical techniques have also been used to keep into account the high number (up to several thousands) of chemical descriptors and fragments that can be used for modeling purposes, with the problem of increase in noise and lack of statistical robustness. Also in this case, linear and nonlinear methods have been used, such as principal component analysis (PCA) and genetic algorithms (GA) [6]. [Pg.186]

Sakawa, M., Inuiguchi, M., Sundad, H., and Sawada, K. (1994), Fuzzy Multiobjective Combinatorial Optimization through Revised Genetic Algorithms, Journal cf Japan Society for Fuzzy Theory and System, Vol. 6, pp. 177-186 (in Japanese). [Pg.2622]

AI approaches to shop floor, 1775-1782 commercial software, 1782 fuzzy set theory, 1781-1782 genetic algorithms (GA), 1780-1781 knowledge-based systems, 1775-1776 neural networks, 1777-1780 in automotive industry, 1734 in aviation industry, 1734-1735 branch and bound, 1728-1729 cyclic, 1746-1747... [Pg.2776]

See other pages where Fuzzy genetic algorithms is mentioned: [Pg.285]    [Pg.285]    [Pg.440]    [Pg.509]    [Pg.509]    [Pg.372]    [Pg.135]    [Pg.138]    [Pg.688]    [Pg.130]    [Pg.273]    [Pg.92]    [Pg.143]    [Pg.336]    [Pg.336]    [Pg.335]    [Pg.28]    [Pg.93]    [Pg.2399]    [Pg.271]    [Pg.465]    [Pg.466]    [Pg.79]    [Pg.55]    [Pg.395]    [Pg.338]    [Pg.19]    [Pg.513]    [Pg.513]    [Pg.69]    [Pg.160]    [Pg.164]    [Pg.2701]    [Pg.2703]    [Pg.2714]    [Pg.3]    [Pg.566]    [Pg.568]   
See also in sourсe #XX -- [ Pg.285 ]



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