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Author Ran, Li Yi ♦ Yong, Zhu Yong
Source CiteSeerX
Content type Text
File Format PDF
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Subject Keyword Time Efficiency ♦ Chaos Particle Swarm ♦ Escape Factor ♦ Algorithm Add Acceleration Factor ♦ Experiment Result ♦ Good Clustering Effect ♦ Chaotic Sequence ♦ High Stability ♦ Clustering Effect ♦ Fast Convergence Speed ♦ Particle Swarm Algorithm ♦ Initial Condition ♦ Cpsokm Algorithm ♦ Local Optimum ♦ Initial Value Sensitivity ♦ Overall Search Capability ♦ Random Value Uncertainty ♦ Initial Value Problem
Abstract Proposed the Algorithm of K-means (CPSOKM) based on Chaos Particle Swarm in order to solve the problem that K-means algorithm sensitive to initial conditions and is easy to influence the clustering effect. On the selection of the initial value problem, algorithm using particle swarm algorithm to balance the random value uncertainty, and then by introducing a chaotic sequence, the particles move speed and position in a redefined, thus solving the initial value sensitivity, while the algorithm with overall search capability, but also to avoid the local optimum. The algorithm add acceleration factor and escape factor in order to improve the time efficiency. Experiment result proved that the CPSOKM algorithm has a fast convergence speed, high stability, and good clustering effect.
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research
Education Level UG and PG ♦ Career/Technical Study