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Improved Quantum Artificial Fish Algorithm Application to Distributed Network Considering Distributed Generation
Joint Authors
Du, Tingsong
Hu, Yang
Ke, Xianting
Source
Computational Intelligence and Neuroscience
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-13, 13 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-09-01
Country of Publication
Egypt
No. of Pages
13
Main Subjects
Abstract EN
An improved quantum artificial fish swarm algorithm (IQAFSA) for solving distributed network programming considering distributed generation is proposed in this work.
The IQAFSA based on quantum computing which has exponential acceleration for heuristic algorithm uses quantum bits to code artificial fish and quantum revolving gate, preying behavior, and following behavior and variation of quantum artificial fish to update the artificial fish for searching for optimal value.
Then, we apply the proposed new algorithm, the quantum artificial fish swarm algorithm (QAFSA), the basic artificial fish swarm algorithm (BAFSA), and the global edition artificial fish swarm algorithm (GAFSA) to the simulation experiments for some typical test functions, respectively.
The simulation results demonstrate that the proposed algorithm can escape from the local extremum effectively and has higher convergence speed and better accuracy.
Finally, applying IQAFSA to distributed network problems and the simulation results for 33-bus radial distribution network system show that IQAFSA can get the minimum power loss after comparing with BAFSA, GAFSA, and QAFSA.
American Psychological Association (APA)
Du, Tingsong& Hu, Yang& Ke, Xianting. 2015. Improved Quantum Artificial Fish Algorithm Application to Distributed Network Considering Distributed Generation. Computational Intelligence and Neuroscience،Vol. 2015, no. 2015, pp.1-13.
https://search.emarefa.net/detail/BIM-1057769
Modern Language Association (MLA)
Du, Tingsong…[et al.]. Improved Quantum Artificial Fish Algorithm Application to Distributed Network Considering Distributed Generation. Computational Intelligence and Neuroscience No. 2015 (2015), pp.1-13.
https://search.emarefa.net/detail/BIM-1057769
American Medical Association (AMA)
Du, Tingsong& Hu, Yang& Ke, Xianting. Improved Quantum Artificial Fish Algorithm Application to Distributed Network Considering Distributed Generation. Computational Intelligence and Neuroscience. 2015. Vol. 2015, no. 2015, pp.1-13.
https://search.emarefa.net/detail/BIM-1057769
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1057769