Multiple birth support vector machine based on dynamic quantum particle swarm optimization algorithm

At present, the parameters of the multiple birth support vector machine (MBSVM) are mainly determined by experience or artificially specified by the grid method. Both of these methods rely too much on the experience value, which is easy to cause the selection of the parameter value to be insufficien...

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Bibliographic Details

Published in:	Neurocomputing (Amsterdam) Vol. 480; pp. 146 - 156
Main Authors:	Ding, Shifei, Zhang, Zichen, Sun, Yuting, Shi, Songhui
Format:	Journal Article
Language:	English
Published:	Elsevier B.V 01.04.2022
Subjects:	Contraction expansion (CE) coefficient Dynamic quantum particle swarm optimization algorithm (DQPSO) Multiple birth support vector machine (MBSVM) Parameter optimization Multiple birth support vector machine (MBSVM) Contraction expansion (CE) coefficient Dynamic quantum particle swarm optimization algorithm (DQPSO) Parameter optimization
ISSN:	0925-2312, 1872-8286
Online Access:	Get full text
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