DocumentCode
3345284
Title
Notice of Retraction
Particle swarm optimization based on catfish effect for flood optimal operation of reservoir
Author
Changming Ji ; Fang Liu ; Xinming Zhang
Author_Institution
Renewable Energy Sch., North China Electr. Power Univ., Beijing, China
Volume
2
fYear
2011
fDate
26-28 July 2011
Firstpage
1197
Lastpage
1201
Abstract
Notice of Retraction
After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.
We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.
The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.
In the light of the characteristics of the reservoir flood optimal operation, such as multi-restriction, multi-dimension, non-linearity and difficult algorithms, the catfish effect mechanism is introduced into the particle swarm optimization and named catfish effect particle swarm optimization. The arithmetic introduced catfish particles through the startup device of catfish and adjusted the flying pattern of particle swarm by the catfish effect in the progress of evolutionary. On the one hand, the driven influence of catfish particles forces the swarm out of steady-state and inspired its vitality in order to improve the diversity of particle swarm; on the other hand, take the advantage of the high quality of dynamics adjustment of catfish, the arithmetic aim to guide the optimization and hence keep its high search performance. Calculation results show that compared with the standard particle swarm optimization and the chaotic particle swarm optimization, the catfish effect particle swarm optimization has the better overall searching capability and faster convergence speed, which can be effectively applied to the reservoir flood optimal operation.
After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.
We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.
The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.
In the light of the characteristics of the reservoir flood optimal operation, such as multi-restriction, multi-dimension, non-linearity and difficult algorithms, the catfish effect mechanism is introduced into the particle swarm optimization and named catfish effect particle swarm optimization. The arithmetic introduced catfish particles through the startup device of catfish and adjusted the flying pattern of particle swarm by the catfish effect in the progress of evolutionary. On the one hand, the driven influence of catfish particles forces the swarm out of steady-state and inspired its vitality in order to improve the diversity of particle swarm; on the other hand, take the advantage of the high quality of dynamics adjustment of catfish, the arithmetic aim to guide the optimization and hence keep its high search performance. Calculation results show that compared with the standard particle swarm optimization and the chaotic particle swarm optimization, the catfish effect particle swarm optimization has the better overall searching capability and faster convergence speed, which can be effectively applied to the reservoir flood optimal operation.
Keywords
convergence; floods; particle swarm optimisation; reservoirs; search problems; catfish effect particle swarm optimization; chaotic particle swarm optimization; flying pattern; reservoir flood optimal operation; Convergence; Floods; Heuristic algorithms; Optimization; Particle swarm optimization; Reservoirs; catfish effect; flood optimal operation; particle swarm optimization algorithm;
fLanguage
English
Publisher
ieee
Conference_Titel
Natural Computation (ICNC), 2011 Seventh International Conference on
Conference_Location
Shanghai
ISSN
2157-9555
Print_ISBN
978-1-4244-9950-2
Type
conf
DOI
10.1109/ICNC.2011.6022233
Filename
6022233
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