The Application of Improved Dynamic Decision Tree Based on Particle Swarm Optimization during Transportation Process

Abstract:

For the relationship of environmental parameters and variables in the each transport process, by using data mining, the system gets the corresponding decision tree. In a certain environment parameters conditions, the occurrence of the event is determined by the decision tree. Through the No Free Lunch Theorem (NFL) revelation, the original PSO algorithm is improved to enhance the validity of the original decision tree. To the final experiments results, once again demonstrate the improved algorithm is efficient.

• Periodical: Advanced Materials Research (Volume 936)
• Pages: 2247-2253
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.936.2247
• Online since: June 2014
• Authors: Xin Hai Li*, Li Li, Xing Fu
• Keywords: Data Mining (DM), Decision Tree, ID3, Particle Swarm Optimization Algorithm, Transportation

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