Application of Artificial Fish Swarm Algorithm in Radial Basis Function Neural Network

Zhou, Yuhong; Duan, Jiguang; Shao, Limin

doi:10.12928/telkomnika.v14i2.2752

TELKOMNIKA

2016

DOI: 10.12928/telkomnika.v14i2.2752

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Application of Artificial Fish Swarm Algorithm in Radial Basis Function Neural Network

Yuhong Zhou

Jiguang Duan

Limin Shao

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2018

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References 8 publications

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Using Multi-objective Artificial Fish Swarm Algorithm to Solve the Software Project Scheduling Problem

Almshhadany¹,

Ibrahim²

2018

IJCA

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In this paper, a new multi-objective artificial fish swarm algorithm was proposed based on the principles of PAES algorithm and it is used to solve SPSP. The aim of this proposal is to solve the software project scheduling problem with artificial fish swarm algorithm and to overcome some disadvantages that AFSA suffer from. The performance of the proposed algorithm was compared with another multiobjective AFSA based on the use of global information (GAFSA), in terms of speed, quality of produced solutions and complexity of algorithm operations. The results show that the proposed algorithm is faster, easier to implement, require less computations, and had obtained better nondominated solutions than the other algorithm.

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Using Multi-objective Artificial Fish Swarm Algorithm to Solve the Software Project Scheduling Problem

Almshhadany¹,

Ibrahim²

2018

IJCA

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Application of Artificial Fish Swarm Algorithm in Radial Basis Function Neural Network

Abstract: Abstract

Cited by 1 publication

References 8 publications

Using Multi-objective Artificial Fish Swarm Algorithm to Solve the Software Project Scheduling Problem

Using Multi-objective Artificial Fish Swarm Algorithm to Solve the Software Project Scheduling Problem

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