Computational Intelligence in ControlMohammadian, Masoud, Sarker, Rahul A., Yao, Xin The problem of controlling uncertain dynamic systems, which are subject to external disturbances, uncertainty and sheer complexity is of considerable interest in computer science, Operations Research and Business domains. The application of intelligent systems has been found useful in problems when the process is either difficult to model or difficult to solve by conventional methods. Intelligent systems have attracted increasing attention in recent years for solving many complex problems. Computational Intelligence in Control will be a repository for the theory and applications of intelligent systems techniques in modelling control and automation. |
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activity adaptive agencies agents analysis application approach Artificial assignment Bayesian behavior calculated chapter clustering complex Computer Conference considered crossover decision defined described determine developed distribution dynamic effect Engineering ensemble environment evaluation evolution evolutionary algorithm example experiments Figure final fitness frequency function fuzzy logic genetic algorithms given glide slope implemented important increase indicates individual initial input Intelligence interests International knowledge layer learning machine mean measure methods mutation negative correlation neural network nodes objective obtained ofthe operators optimization output parameters path pattern performance perturbation pilot population position possible prediction presented problem Proceedings proposed recombination represents respectively response robot robustness rules samples Science selection shows simulation solutions solve space speed starting strategy structure Table task techniques theory tree units University values variables weights wind
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Business Applications and Computational Intelligence Kevin E. Voges,Nigel Pope No preview available - 2006 |