Hybrid intelligent deep kernel incremental extreme learning machine based on differential evolution and multiple population grey wolf optimization methods

Hybrid intelligent deep kernel incremental extreme learning machine based on differential evolution and multiple population grey wolf optimization methods

Focussing on the problem that redundant nodes in the kernel incremental extreme learning machine (KI-ELM) which leads to ineffective iteration increase and reduce the learning efficiency, a novel improved hybrid intelligent deep kernel incremental extreme learning machine (HI-DKIELM) based on a hybr...

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Bibliographic Details
Main Authors: Di Wu, Zong Shun Qu, Feng Jiao Guo, Xiao Lin Zhu, Qin Wan
Format: Article
Language:English
Published: Taylor & Francis Group 2019-01-01
Series:Automatika
Subjects:
Extreme learning machine (ELM)
kernel incremental extreme learning machine (KIELM)
differential evolution (DE)
multiple population grey wolf optimization methods (MPGWO)
hybrid intelligence (HI)
Online Access:http://dx.doi.org/10.1080/00051144.2019.1570642

Internet

http://dx.doi.org/10.1080/00051144.2019.1570642

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