The use of machine and deep learning to model the relationship between discomfort temperature and labor productivity loss among petrochemical workers

• Hlavní autoři: Yilin Zhang (Autor), Yifeng Chen (Autor), Qingling Su (Autor), Xiaoyin Huang (Autor), Qingyu Li (Autor), Yan Yang (Autor), Zitong Zhang (Autor), Jiake Chen (Autor), Zhihong Xiao (Autor), Rong Xu (Autor), Qing Zu (Autor), Shanshan Du (Autor), Wei Zheng (Autor), Weimin Ye (Autor), Jianjun Xiang (Autor)
• Médium: Kniha
• Vydáno: BMC, 2024-11-01T00:00:00Z.
• Témata: article
• On-line přístup: Connect to this object online.

Abstract Background Workplace may not only increase the risk of heat-related illnesses and injuries but also compromise work efficiency, particularly in a warming climate. This study aimed to utilize machine learning (ML) and deep learning (DL) algorithms to quantify the impact of temperature discom...