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<div><p>The frequent bending of shearer cables during operation often leads to mechanical fatigue, posing risks to equipment safety. Accurately predicting the mechanical properties of these cables under bending conditions is crucial for improving the reliability and service life of shear...

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Bibliographic Details
Main Author:	Lijuan Zhao (1387689) (author)
Other Authors:	Dongyang Wang (134365) (author), Guocong Lin (20670952) (author), Shuo Tian (4516609) (author), Hongqiang Zhang (8616087) (author), Yadong Wang (82064) (author)
Published:	2025
Subjects:	Biophysics Biological Sciences not elsewhere classified Information Systems not elsewhere classified temporal convolutional network operation often leads mean squared error mean absolute error dilated convolution operations assign adaptive weights cable conductors based complex operating conditions bidirectional information processing stress variation patterns div >< p term sequential features seattention ), referred improving cable management control conductor features shearer intelligent cables shearer cable control conductor term memory sequence information intelligent development bending conditions shearer cables seattention model seattention mechanism rmse ), power conductor key features input features traction speeds substantial influence shap value shap ). service life results show research shows posing risks paper proposes optical fiber novel approach model ’ mechanical properties mechanical fatigue mechanical characteristics maximum deviation frequent bending excitation attention equipment safety effectively enhancing conducted using coal mines capture long bilstm ), actual values accurately predicting
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