Method of calculating model similarity based on genetic annealing algorithm

被引：0
|
作者：
Gao X. [1 ]
Tan T. [1 ]
Zhang C. [2 ]
机构：
[1] School of Computer Science and Technology, Harbin University of Science and Technology, Harbin
[2] School of Software and Microelectronics, Harbin University of Science and Technology, Harbin
来源：
Zhang, Chunxiang (z6c6x666@163.com) | 1600年 / Editorial Board of Journal of Harbin Engineering卷 / 41期
关键词：
Adjacency relation; Genetic algorithm; Genetic annealing algorithm; Global similarity matrix; Matching sequence of faces; Shape similarity; Simulated annealing algorithm; Structure similarity;
D O I：
10.11990/jheu.201901093
中图分类号：
学科分类号：
摘要：
To retrieve the most identical CAD model, this study proposes a model similarity calculation method based on a genetic annealing algorithm, which combines the global searching ability of a genetic algorithm and the local searching ability of a simulated annealing algorithm. The difference of the faces' edge numbers is applied to compute the shape similarity between source and target faces. The shape similarity and adjacency relation of the faces are combined to calculate the structural similarity. Based on the shape and structural similarities of faces, a global similarity matrix of two models is constructed. The genetic annealing algorithm is used to find an optimal matching sequence of faces between the two models. Based on this optimal matching sequence of faces, the similarity of two models is calculated. Experimental results show that compared with simulated annealing algorithm, the proposed method improves the ranking effect of 13.33% of models, which proves that it can measure the difference of two models accurately. © 2020, Editorial Department of Journal of HEU. All right reserved.
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页码：1073 / 1079
页数：6
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