A Memetic Differential Evolution in Filter Design for Defect Detection in Paper Production
作者： Ville Tirronen , Ferrante Neri , Tommi Karkkainen , Kirsi Majava , Tuomo Rossi
DOI: 10.1007/978-3-540-71805-5_35
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摘要: This article proposes a Memetic Differential Evolution (MDE) for designing digital filters which aim at detecting defects of the paper produced during an industrial process. The MDE is adaptive evolutionary algorithm combines powerful explorative features (DE) with exploitative two local searchers. searchers are adaptively activated by means novel control parameter measures fitness diversity within population. Numerical results show that DE framework efficient class problems under study and employment helpful in supporting mechanism avoiding stagnation thus solutions having high performance.
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