An Optimization Method of Knowledge Mapping Relationship Based on Improved Ant Colony Algorithm

被引：0

作者：

Xu, Shi-Fu ^{[1
,2
]}

Jiang, Ya-Nan ^{[1
]}

机构：

[1] Faculty of Mechanical Engineering and Automation, College of Science and Technology of Ningbo University, Ningbo, China

[2] Faculty of Mechanical Engineering & Automation, Zhejiang Sci-Tech University, Hangzhou, China

来源：

Journal of Computers (Taiwan) | 2022年 / 33卷 / 02期

关键词：

Ant colony optimization;

D O I：

10.53106/199115992022043302012

中图分类号：

学科分类号：

摘要：

The current knowledge mapping relationship optimization methods cannot obtain high-precision information. An optimization method of knowledge mapping relationship based on improved ant colony algorithm is proposed. The high-precision information of the network is obtained by using the cyclic network. The SGP problem is used to replace the optimization problem of the knowledge map relationship. The optimization objective function of the knowledge map relationship is constructed and solved by the improved ant colony algorithm. The optimization of the knowledge map relationship is realized. Experimental results show that the proposed method has high average accuracy, high knowledge accuracy and high knowledge coverage. © 2022 Computer Society of the Republic of China. All rights reserved.

引用

页码：137 / 147