Titlebook: Computational Intelligence Systems in Industrial Engineering; With Recent Theory a Cengiz Kahraman Book 2012 Atlantis Press 2012 Computer s

耕種

indigenous

Fuzzy Simulation Based Chance ConstrainedProgramming,r by means of fuzzy simulation. This chapter addresses fuzzy simulation which is used for estimating the possibility (credibility) of the constraints, and genetic algorithm (GA) which is applied as an optimization heuristic. Four numerical examples are given at the end of the chapter to illustrate the utilization of the specified methods.

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Using Fuzzy Cognitive Maps as a Modeling Tool for Traveler Satisfaction in Public Transit Systems,ed to relations to represent the strength of impact. The value of factors are updated periodically by formulating the system in an iterative process. This is helpful in giving us the ability to see the system changes caused by the changes in factors.

Emg827

Development of a Deformable Exit Opticve influence of each factor on every other factor with which it interacts. As its comparison to current methods demonstrates, the method successfully derives meaningful priorities from complex and uncertain decision structures.

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Comedienne

https://doi.org/10.1007/978-981-10-1448-2cient algorithm for mining such rules. We show an extension to the dynamic case of by using linguistic summaries of times series data. As an example we show the use of linguistic summaries for Web server log analysis, in both the static and dynamic case. The results can be useful for the design and maintenance of computer networks.

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MORPH

Affection