An enhanced memetic differential evolution in filter design for defect detection in paper production.

De Montfort University Open Research Archive

Show simple item record Tirronen, Ville en Neri, Ferrante en K¨arkk¨ainen, Tommi en Majava, Kirsi en Rossi, Tuomo en 2012-04-11T09:41:36Z 2012-04-11T09:41:36Z 2008
dc.identifier.citation Tirronen, V., Neri, F., Kärkkäinen, T., Majava, K. and Rossi, T. (2008) An Enhanced Memetic Differential Evolution in Filter Design for Defect Detection in Paper Production. Evolutionary Computation Journal, 16 (4), pp. 529-555 en
dc.identifier.issn 1063-6560
dc.description.abstract This article proposes an Enhanced Memetic Differential Evolution (EMDE) for designing digital filters which aim at detecting defects of the paper produced during an industrial process. Defect detection is handled by means of two Gabor filters and their design is performed by the EMDE. The EMDE is a novel adaptive evolutionary algorithm which combines the powerful explorative features of Differential Evolution with the exploitative features of three local search algorithms employing different pivot rules and neighborhood generating functions. These local search algorithms are the Hooke Jeeves Algorithm, a Stochastic Local Search, and Simulated Annealing. The local search algorithms are adaptively coordinated by means of a control parameter that measures fitness distribution among individuals of the population and a novel probabilistic scheme. Numerical results confirm that Differential Evolution is an efficient evolutionary framework for the image processing problem under investigation and show that the EMDE performs well. As a matter of fact, the application of the EMDE leads to a design of an efficiently tailored filter. A comparison with various popular metaheuristics proves the effectiveness of the EMDE in terms of convergence speed, stagnation prevention, and capability in detecting solutions having high performance. en
dc.language.iso en en
dc.publisher MIT Press en
dc.subject memetic algorithms en
dc.subject differential evolution en
dc.subject multimeme algorithms en
dc.subject digital filter design en
dc.subject FIR filter en
dc.subject paper production en
dc.subject edge detection en
dc.title An enhanced memetic differential evolution in filter design for defect detection in paper production. en
dc.type Article en
dc.researchgroup Centre for Computational Intelligence en

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