Study on typical process route mining method based on multilevel longest common subsequence information entropy and intelligent clustering model-Reference-Cited by-同舟云学术

Study on typical process route mining method based on multilevel longest common subsequence information entropy and intelligent clustering model

Published:2023-02-10 Issue:10 Volume:36 Page:1416-1430
ISSN:0951-192X
Container-title:International Journal of Computer Integrated Manufacturing
language:en
Short-container-title:International Journal of Computer Integrated Manufacturing

Author:

Chunlei Li¹²^ORCID

Affiliation:

1. School of mechanical engineering, Baoji University of Arts and Sciences, Baoji, China

2. Shaanxi Key Laboratory of Advanced Manufacturing and Evaluation of Robot Key Components, Baoji University of Arts and Sciences, Baoji, China

Funder

Research and Development

Zhejiang University

the Scientific Research Program funded by Shaanxi Provincial Education Department

Publisher

Informa UK Limited

Subject

Electrical and Electronic Engineering,Computer Science Applications,Mechanical Engineering,Aerospace Engineering

Link

https://www.tandfonline.com/doi/pdf/10.1080/0951192X.2023.2177745

Reference25 articles.

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5. Fan, W., Y. Zhang, L. Wang, and S. Zhong. 2018. “Typical Machining Process Mining of Servo Valve Parts Based on Self-Adaptive Affinity Propagation Clustering.” In Proceedings IEEE International Computers, Signals and Systems Conference, Dalian, China, 674–678.