MCS-HMS: A Multi-Cluster Selection Strategy for the Human Mental Search Algorithm-Reference-Cited by-同舟云学术

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MCS-HMS: A Multi-Cluster Selection Strategy for the Human Mental Search Algorithm

Published:2021-12-05 Issue: Volume: Page:
ISSN:
Container-title:2021 IEEE Symposium Series on Computational Intelligence (SSCI)
language:
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Author:

Bojnordi Ehsan¹,Mousavirad Seyed Jalaleddin²,Schaefer Gerald³,Korovin Iakov⁴

Affiliation:

1. Iranian National Tax Administration,Information Technology Department,Bojnord,Iran

2. Hakim Sabzevari University,Computer Engineering Department,Sabzevar,Iran

3. Loughborough University,Department of Computer Science,Loughborough,U.K.

4. Southern Federal University,Taganrog,Russia

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9659537/9659538/09660143.pdf?arnumber=9660143

Reference24 articles.

1. Human mental search: a new population-based metaheuristic optimization algorithm

2. Human mental search-based multilevel thresholding for image segmentation

3. An efficient method to minimize cross-entropy for selecting multi-level threshold values using an improved human mental search algorithm

4. Colour Quantisation by Human Mental Search

5. Colour Quantisation using Human Mental Search and Local Refinement

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2. A Novel Two-Level Clustering-Based Differential Evolution Algorithm for Training Neural Networks;Lecture Notes in Computer Science;2024

3. A New Hybrid Method for Text Feature Selection Through Combination of Relative Discrimination Criterion and Ant Colony Optimization;Proceedings of 7th International Conference on Harmony Search, Soft Computing and Applications;2022

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