6533b7ddfe1ef96bd127516b

RESEARCH PRODUCT

A Memetic Differential Evolution in Filter Design for Defect Detection in Paper Production

Tuomo RossiVille TirronenKirsi MajavaFerrante NeriTommi Kärkkäinen

subject

Engineeringeducation.field_of_studyFinite impulse responsebusiness.industryProcess (engineering)PopulationEvolutionary algorithmMachine learningcomputer.software_genreFilter designDifferential evolutionMemetic algorithmArtificial intelligencebusinesseducationcomputerDigital filter

description

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 an adaptive evolutionary algorithm which combines the powerful explorative features of Differential Evolution (DE) with the exploitative features of two local searchers. The local searchers are adaptively activated by means of a novel control parameter which measures fitness diversity within the population. Numerical results show that the DE framework is efficient for the class of problems under study and employment of exploitative local searchers is helpful in supporting the DE explorative mechanism in avoiding stagnation and thus detecting solutions having a high performance.

yearjournalcountryeditionlanguage
2007-06-20
https://doi.org/10.1007/978-3-540-71805-5_35