Modeling of EDM responses by support vector machine regression with parameters selected by particle swarm optimization

DOI10.1016/J.APM.2013.10.073zbMath1449.62198OpenAlexW1990565902MaRDI QIDQ1630717

Ushasta Aich, Simul Banerjee

Publication date: 10 December 2018

Published in: Applied Mathematical Modelling (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.apm.2013.10.073

zbMATH Keywords

particle swarm optimization (PSO)support vector machine (SVM)electrical discharge machining (EDM)

Mathematics Subject Classification ID

Inference from stochastic processes and prediction (62M20) Learning and adaptive systems in artificial intelligence (68T05) Problem solving in the context of artificial intelligence (heuristics, search strategies, etc.) (68T20)

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Cites Work

• Unnamed Item
• Study of the parameters in electrical discharge machining through response surface methodology approach
• Practical selection of SVM parameters and noise estimation for SVM regression
• Multi-objective particle swarm optimization with time variant inertia and acceleration coefficients

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