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Self-adaptive Differential Evolution with Modified Multi-Trajectory Search for CEC’2010 Large Scale Optimization Read chapter Read first chapter

2010 | OriginalPaper | Chapter

Using Social Emotional Optimization Algorithm to Direct Orbits of Chaotic Systems

Authors : Zhihua Cui, Zhongzhi Shi, Jianchao Zeng

Published in: Swarm, Evolutionary, and Memetic Computing

Publisher: Springer Berlin Heidelberg

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Social emotional optimization algorithm (SEOA) is a new novel population-based stochastic optimization algorithm. In SEOA, each individual simulates one natural person. All of them are communicated through cooperation and competition to increase social status. The winner with the highest status will be the final solution. In this paper, SEOA is employed to solve the directing orbits of chaotic systems, simulation results show this new variant increases the performance significantly when compared with particle swarm optimization algorithm.

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previous chapter A Hybrid GA-Adaptive Particle Swarm Optimization Based Tuning of Unscented Kalman Filter for Harmonic Estimation
next chapter A Hybrid ANN-BFOA Approach for Optimization of FDM Process Parameters
Metadata
Title
Using Social Emotional Optimization Algorithm to Direct Orbits of Chaotic Systems
Authors
Zhihua Cui
Zhongzhi Shi
Jianchao Zeng
Copyright Year
2010
Publisher
Springer Berlin Heidelberg
Book
Swarm, Evolutionary, and Memetic Computing

Print ISBN: 978-3-642-17562-6

Electronic ISBN: 978-3-642-17563-3

Copyright Year: 2010

DOI
https://doi.org/10.1007/978-3-642-17563-3_47

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