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This paper proposes a novel evolutionary computation (EC) algorithm, fuzzy scaled mutation evolutionary computation (FSMEC), for solving nonlinear numerical optimization problems. Although EC has been typically used for obtaining nonlinear optimal solutions for several years, users are required to determine the parameters of the algorithm. In this study, a fuzzy inference system (FIS) was used to...
This study addresses a blind image deconvolution which uses only blurred image and tiny point spread function (PSF) information to restore the original image. In order to mitigate the problem trapping into a local solution in conventional algorithms, the evolutionary learning is reasonably to apply to this task. In this paper, particle swarm optimization (PSO) is therefore utilized to seek the unknown...
In multi-objective particle swarm optimization (MOPSO) methods, selecting the best local guide (the global best particle) for each particle of the population provides great benefits on the convergence and diversity of solutions, especially when problems are optimized with a large number of objectives. This paper introduces the proportional distribution based particle swarm optimizer (PSO) with cross-over...
The purpose of this paper is to search the best flight route efficiently for unmanned aerial vehicle (UAV) in the 3-dimention complicated topography. The proposed method for the best flight route is mainly utilizing evolutionary algorithm, and give the proper initial population of evolutionary algorithm through skeletonization, efficient pre-processing procedure. In order to provide a smooth flight...
Noise reduction problem is addressed by this study. Recently, wavelet thresholding has become popular and has gotten much attention among a number of de-noisy approaches. The most of threshold determination are developed from universal method proposed by Donoho. But, some shortcomings of the determination are caused from several incorrectly estimated factors and the lack of adaptability for whole...
As more and more real-world optimization problems become increasingly complex, algorithms with more capable optimizations are also increasing in demand. For solving large scale global optimization problems, this paper presents a variation on the traditional PSO algorithm, called the efficient population utilization strategy for particle swarm optimizer (EPUS-PSO). This is achieved by using variable...
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