A data-driven state identification method for intelligent control of the joint station export system

A data-driven state identification method for intelligent control of the joint station export system

Abstract As a necessary part of intelligent control of a joint station, the automatic identification of abnormal conditions and automatic adjustment of operation schemes need to judge the running state of the system. In this paper, a combination of Particle Swarm Optimization (PSO) and Gray Wolf Opt...

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Bibliographic Details
Main Authors: Guangli Xu, Yifu Wang, Zhihao Zhou, Yifeng Lu, Liangxue Cai
Format: Article
Language:English
Published: Nature Portfolio 2025-01-01
Series:Scientific Reports
Subjects:
State identification
Parameter prediction
GWO
PSO
BP neural network
Online Access:https://doi.org/10.1038/s41598-025-87283-2
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https://doi.org/10.1038/s41598-025-87283-2

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