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This paper aims at using imperialist competitive algorithm based fuzzy logic (FICA), to control an automatic voltage regulator (AVR) in order to increase the stability and obtain more controllability of the system. For the stabilization of the automatic voltage regulator a proportional-integral-derivative controller (PID) was used. We applied the FICA, which is the combination of the imperialist competitive...
In this paper, we propose an evolutionary algorithm for high dimensional global optimization, which makes use of correlation coefficients, cooperative coevolution and differential evolution (4CDE). The decision variables are associated in high correlated groups, that also change throughout generations, depending on the area being currently explored. Preliminary results are shown for 50 variables....
In this paper, we show the effectiveness of an EMO (Evolutionary Multi-criterion Optimization) algorithm with objective reduction using a correlation-based weighted-sum in many objective knapsack problems. Recently many EMO algorithms are proposed for various multi-objective problems. However, it is known that the convergence performance to the Pareto-frontier becomes weak in approaches using archives...
This paper presents the evolutionary neural network (ENN) model for the prediction of output from a grid-connected photovoltaic system installed at Malaysian Energy Centre (PTM), Bangi, Malaysia. The ENN model had been developed using evolutionary programming (EP) through the optimization of the number of nodes in the hidden layer, the learning rate and the momentum rate. The ENN model employs solar...
Many objective optimization is a natural extension to multi-objective optimization where the number of objectives are significantly more than five. The performance of current state of the art algorithms (e.g. NSGA-II, SPEA2) is known to deteriorate significantly with increasing number of objectives due to the lack of adequate convergence pressure. It is of no surprise that the performance of NSGA-II...
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