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Notice of Violation of IEEE Publication Principles
"A Quadratic Particle Swarm Optimization for Weight Optimization"
by He Jing, Shi Dejia, and Wang Li
in the Proceedings of the 2009 Third International Symposium on Intelligent Information Technology Application (IITA 2009), November 2009, pp. 557-560
After careful and considered review of the content and authorship of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE's Publication Principles.
This paper contains significant portions of original text from the papers cited below. The original text was copied without attribution (including appropriate references to the original author(s) and/or paper titles) and without permission.
Due to the nature of this violation, reasonable effort should be made to remove all past references to this paper, and future references should be made to the following articles:
"A New Optimization Algorithm for Weight Optimization"
by Hui Li and Xuesong Yan
in Lecture Notes in Computer Science, Volume 5370, Springer, 2008, pp. 723-730
Particle Swarm Optimization algorithm was developed under the inspiration of behavior laws of bird flocks, fish schools and human communities. Aiming at the disadvantages of Particle Swarm Optimization algorithm like being trapped easily into a local optimum, this paper improves the standard PSO and proposes a new algorithm to solve the overcomes of the standard PSO. This paper improved the standard PSO's evolution equation on the foundation of analyzing standard PSO's model and its mechanisms, and then presents a Quadratic PSO. The simulation illustrates the Quadratic PSO improves the performance of the PSO We use the new algorithm for the weight optimization in college student evaluation, and compared with PSO; the results show that the new algorithm is efficient.