[1]高雪瑶,谭涛,张春祥.遗传退火算法的模型相似性计算方法[J].哈尔滨工程大学学报,2020,41(7):1073-1079.[doi:10.11990/jheu.201901093]
 GAO Xueyao,TAN Tao,ZHANG Chunxiang.Method of calculating model similarity based on genetic annealing algorithm[J].hebgcdxxb,2020,41(7):1073-1079.[doi:10.11990/jheu.201901093]
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遗传退火算法的模型相似性计算方法(/HTML)
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《哈尔滨工程大学学报》[ISSN:1006-6977/CN:61-1281/TN]

卷:
41
期数:
2020年7期
页码:
1073-1079
栏目:
出版日期:
2020-07-05

文章信息/Info

Title:
Method of calculating model similarity based on genetic annealing algorithm
作者:
高雪瑶1 谭涛1 张春祥2
1. 哈尔滨理工大学 计算机科学与技术学院, 黑龙江 哈尔滨 150080;
2. 哈尔滨理工大学 软件与微电子学院, 黑龙江 哈尔滨 150080
Author(s):
GAO Xueyao1 TAN Tao1 ZHANG Chunxiang2
1. School of Computer Science and Technology, Harbin University of Science and Technology, Harbin 150080, China;
2. School of Software and Microelectronics, Harbin University of Science and Technology, Harbin 150080, China
关键词:
遗传算法模拟退火算法遗传退火算法形状相似性邻接关系结构相似性整体相似度矩阵面匹配序列
分类号:
TP391.7
DOI:
10.11990/jheu.201901093
文献标志码:
A
摘要:
为了检索最相似的CAD模型,本文结合遗传算法的全局搜索能力和模拟退火算法的局部搜索能力,提出了基于遗传退火算法的模型相似性度量方法。利用面的边数差异来计算源模型面与目标模型面之间的形状相似性。结合面的形状相似性和面的邻接关系来计算面的结构相似性。以面的形状相似性和结构相似性为基础,构造2个模型的整体相似度矩阵。利用遗传退火算法对该矩阵进行搜索,得到2个模型之间的最优面匹配序列。以最优面匹配序列为基础,计算2个模型的相似性。实验结果表明:相对于模拟退火算法,本文所提出方法使13.33%的模型的排序效果有所改善。该方法能够更准确地度量2个模型之间的差异。

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备注/Memo

备注/Memo:
收稿日期:2019-01-31。
基金项目:国家自然科学基金项目(61502124,60903082);中国博士后科学基金项目(2014M560249);黑龙江省普通高校基本科研业务费专项资金项目(LGYC2018JC014);黑龙江省自然科学基金项目(F2015041,F201420).
作者简介:高雪瑶,女,教授;张春祥,男,教授.
通讯作者:张春祥,E-mail:z6c6x666@163.com.
更新日期/Last Update: 2020-08-15