Advanced orthogonal learning-driven multi-swarm sine cosine optimization: Framework and case studies-Reference-Cited by-同舟云学术

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Advanced orthogonal learning-driven multi-swarm sine cosine optimization: Framework and case studies

Published:2020-04 Issue: Volume:144 Page:113113
ISSN:0957-4174
Container-title:Expert Systems with Applications
language:en
Short-container-title:Expert Systems with Applications

Author:

Chen Hao,Heidari Ali Asghar^ORCID,Zhao Xuehua,Zhang Lejun,Chen Huiling^ORCID

Funder

National Natural Science Foundation of China

Natural Science Foundation of the Jiangsu Higher Education Institutions

Six Talent Peaks Project in Jiangsu Province

Guangdong Natural Science Foundation

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Science Applications,General Engineering

Reference111 articles.

1. An improved opposition-based sine cosine algorithm for global optimization;Abd Elaziz;Expert Systems with Applications,2017

2. Economic dispatch using chaotic bat algorithm;Adarsh;Energy,2016

3. KEEL: A software tool to assess evolutionary algorithms for data mining problems;Alcalá-Fdez;Soft Computing,2009

4. A deep evolutionary approach to bioinspired classifier optimisation for brain-machine interaction;Bird;Complexity,2019

5. Evolving an optimal kernel extreme learning machine by using an enhanced grey wolf optimization strategy;Cai;Expert Systems with Applications,2019

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