A New Model of Projection Pursuit Grade Evaluation Model Based on Simulated Annealing Ant Colony Optimization Algorithm
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.
Year of publication: |
2018
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Authors: | Zhaomei, Gai ; Rentao, Liu ; Qiuxiang, Jiang |
Published in: |
International Journal of Cognitive Informatics and Natural Intelligence (IJCINI). - IGI Global, ISSN 1557-3966, ZDB-ID 2381006-3. - Vol. 12.2018, 4 (01.10.), p. 69-80
|
Publisher: |
IGI Global |
Subject: | Ant Colony Optimization Algorithm (ACO) | Projection Pursuit Grade Evaluation Model (PPE) | Quality Evaluation | Simulated Annealing Algorithm (SA) |
Saved in:
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