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

被引：1
|
作者：
Gai Zhaomei [1 ]
Liu Rentao [2 ]
Jiang Qiuxiang [1 ]
机构：
[1] Northeast Agr Univ, Coll Water Conservancy & Civil Engn, Harbin, Heilongjiang, Peoples R China
[2] Heilongjiang Inst Construct Technol, Dept Municipal & Environm Engn, Harbin, Heilongjiang, Peoples R China
来源：
INTERNATIONAL JOURNAL OF COGNITIVE INFORMATICS AND NATURAL INTELLIGENCE | 2018年 / 12卷 / 04期
基金：
中国国家自然科学基金; 黑龙江省自然科学基金;
关键词：
Ant Colony Optimization Algorithm (ACO); Projection Pursuit Grade Evaluation Model (PPE); Quality Evaluation; Simulated Annealing Algorithm (SA);
D O I：
10.4018/IJCINI.2018100104
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
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.
引用
收藏
页码：69 / 80
页数：12
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