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A New Model of Projection Pursuit Grade Evaluation Model Based on Simulated Annealing Ant Colony Optimization Algorithm

Author

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  • Gai Zhaomei

    (College of Water Conservancy and Civil Engineering, Northeast Agricultural University, Harbin, China)

  • Liu Rentao

    (Department of Municipal and Environmental Engineering, Heilongjiang Institute of Construction Technology, China)

  • Jiang Qiuxiang

    (College of Water Conservancy and Civil Engineering, Northeast Agricultural University, Harbin, China)

Abstract

Projection pursuit model (PP) is widely used in many fields, especially quality evaluation. One of the biggest shortages of PP was that the projection direction is strongly influenced by relevant parameters. In order to solve this problem, many experts and scholars introduced all kinds of parameters optimization method in PP. Based on the basis of previous studies, the article proposed a new model of projection pursuit grade evaluation model (PPE) integrated with simulated annealing ant colony optimization algorithm (SA-ACO). It provided a new thought and method for quality evaluation research. The case example demonstrated that the accuracy and the effect evaluation of the model was effectively and more objectively and practical in the evaluation of quality.

Suggested Citation

  • Gai Zhaomei & Liu Rentao & Jiang Qiuxiang, 2018. "A New Model of Projection Pursuit Grade Evaluation Model Based on Simulated Annealing Ant Colony Optimization Algorithm," International Journal of Cognitive Informatics and Natural Intelligence (IJCINI), IGI Global, vol. 12(4), pages 69-80, October.
    • Handle: RePEc:igg:jcini0:v:12:y:2018:i:4:p:69-80
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