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A Social Tagging Recommendation Model Based on Improved Artificial Fish Swarm Algorithm and Tensor Decomposition Read chapter Read first chapter

2018 | OriginalPaper | Chapter

Compact Cat Swarm Optimization Algorithm

Authors : Ming Zhao, Jeng-Shyang Pan, Shuo-Tsung Chen

Published in: Security with Intelligent Computing and Big-data Services

Publisher: Springer International Publishing

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Abstract

A compact cat swarm optimization algorithm (cCSO) was proposed in this paper. it keeps the same search logic of cat swarm optimization (CSO), i.e. tracing mode and seeking mode, on the other hands, cCSO inherits the main feature of compact optimization algorithms, a normal probabilistic vector is used to generate new individuals, the mean and the standard deviation of the probabilistic model could lead cats to the searching direction in next step. Only a cat is adopted in the algorithm, thus, it could run with modest memory requirement. Experimental results show that cCSO has better performance than some compact optimization algorithms in some benchmark functions test. The convergence rate is also a highlight among compact optimization algorithms.

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Metadata
Title
Compact Cat Swarm Optimization Algorithm
Authors
Ming Zhao
Jeng-Shyang Pan
Shuo-Tsung Chen
Copyright Year
2018
Book
Security with Intelligent Computing and Big-data Services

Print ISBN: 978-3-319-76450-4

Electronic ISBN: 978-3-319-76451-1

Copyright Year: 2018

DOI
https://doi.org/10.1007/978-3-319-76451-1_4

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