Abstract
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. The new algorithm keeps not only the fast convergence speed characteristic of PSO, but effectively improves the capability of overall searching as well. 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.
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Li, H., Yan, X. (2008). A New Optimization Algorithm for Weight Optimization. In: Kang, L., Cai, Z., Yan, X., Liu, Y. (eds) Advances in Computation and Intelligence. ISICA 2008. Lecture Notes in Computer Science, vol 5370. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-92137-0_79
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DOI: https://doi.org/10.1007/978-3-540-92137-0_79
Publisher Name: Springer, Berlin, Heidelberg
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