Improve the Performance of a Complex FMS with a Hybrid Machine Learning Algorithm

ISSN Print: 1945-3116
ISSN Online: 1945-3124
www.scirp.net/journal/jsea
E-mail: [email protected]

Citations

"Improve the Performance of a Complex FMS with a Hybrid Machine Learning Algorithm"
written by Hang Li,
published by Journal of Software Engineering and Applications, Vol.10 No.3, 2017

has been cited by the following article(s):

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[1]	Applications of Machine Learning Across Smart Manufacturing, Healthcare, Finance, Computer Vision, Robotics, and Environmental & Sustainability: A Systematic Literature Review Applied Sciences, 2026 DOI:10.3390/app16136574

[2]	Machine learning-supported manufacturing: a review and directions for future research Production & Manufacturing Research, 2024 DOI:10.1080/21693277.2024.2326526

[3]	AHI: a hybrid machine learning model for complex industrial information systems Journal of Combinatorial Optimization, 2023 DOI:10.1007/s10878-023-00988-w

[4]	Model-based routing in flexible manufacturing systems at - Automatisierungstechnik, 2019 DOI:10.1515/auto-2018-0108