...Vasile Georgescu Purpose Type-2 fuzzy sets became attractive in practice because of their footprint of uncertainty that gives them more degrees of freedom. This paper aims to use genetic algorithms (GAs) to design an interval Type-2 fuzzy logic system (IT2FLS) for the purpose of predicting...

... performance of neural network (NN) combined with expert knowledge (EK) to obtain the objective function, and secondly searches the optimal influential parameters with genetic algorithm (GA). Findings Peaks function inside Matlab and the acural application of comprehensive performance optimization...

..., and explore the inner mechanism and optimization strategies of value creation in manufacturing clusters from the perspective of cluster's value activity network. Design/methodology/approach This paper applies a genetic algorithm to optimally search in the target space, and repeatedly exerts genetic...

... a high performance genetic algorithm for community formation based on collective intelligence capacity. An experimental study is presented to illustrate the algorithm. Findings Collective intelligence does not represent the sum of individual intelligences, it is the ability of the community...

... that have contributed to the agent's survival to be used more often. However, this will only select the best rules from the currently available set. The problem remains as to how the agent can discover better rules than those it currently uses. Genetic algorithms follow a Darwinian metaphor...

...Sung‐Kwun Oh; Witold Pedrycz A comprehensive design methodology of hybrid fuzzy controllers (HFC) is proposed. The HFC comes in a form of a convex combination of a standard PID controller and a fuzzy controller. The design procedure dwells on the use of evolutionary computing (genetic algorithm...

... to present an other new kind of genetic algorithms, resulting from the integration of the recursivity in the basis functioning of genetic algorithms, and that we have named Recursive Genetic Algorithm. © MCB UP Limited 2002 Genetic algorithms Prototyping Cybernetics It is generally...

... are also provided. © MCB UP Limited 2001 Cybernetics Computation Genetic algorithms Non‐linear programming In this paper we provide new evidence on the performance of a multipurpose parallel genetic hybrid algorithm (GHA) for nonlinear, non‐convex programming problems. GHA has...

... Keywords: Publication, Cybernetics, Genetic algorithms, Optimisation This is a book that covers the four optimisation techniques that have been described as "intelligent". That is: genetic algorithms, tabu search,simulated annealing and neural networks. Readers of this journal...

... Genetic algorithms Software Intelligent systems have been developed in many application domains, such as intelligent control. Typically these have attempted to reproduce many features usually associated with human faculties such as cognition, learning from experience, and generalisation...

... applied to transient control of λ. In this paper, transient conditions are simulated when the engine crankshaft speed is fixed at 2,500 rpm and the position of the throttle plate angle is varied. © MCB UP Limited 2000 Artificial intelligence Cybernetics Fuzzy logic Genetic algorithms...

...Hojjat Adeli Cybernetics Fuzzy systems Genetic algorithms Neural networks Publication This is a book that will be of interest to cyberneticians and systemists. Its contents list which is included below shows a wide range of interconnecting topics that form important studies...

... P_m of crossover and mutation respectively. Genetic algorithms are sensitive to the definition and the maintenance of population size. As to maintaining versatility of individuals in size so as not to trap into local solution, it seems better that the size is larger. But this will increase computation...