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An Enhanced Osprey Optimization-Based Interpretable Deep Learning Framework for Predicting Coal Spontaneous Combustion Temperatures

Rui Yan Botao Fan Xueqi Qu Cuihuan Ren Xu Zhou

Computers, Materials & Continua2026，Vol.89Issue(10)：P.876-902,27.

Computers, Materials & Continua2026，Vol.89Issue(10)：P.876-902,27.DOI:10.32604/cmc.2026.085749

An Enhanced Osprey Optimization-Based Interpretable Deep Learning Framework for Predicting Coal Spontaneous Combustion Temperatures

Rui Yan ¹Botao Fan ²Xueqi Qu ²Cuihuan Ren ¹Xu Zhou¹

作者信息

1. College of Science,North China University of Science and Technology,Tangshan,China
2. School of Emergency Management and Safety Engineering,North China University of Science and Technology,Tangshan,China
折叠

摘要

关键词

Coal spontaneous combustion/coal mine safety/interpretable deep learning/temperature prediction/BiLSTM/improved osprey optimization algorithm/SHAP analysis

分类

矿业与冶金

引用本文复制引用

Rui Yan,Botao Fan,Xueqi Qu,Cuihuan Ren,Xu Zhou..An Enhanced Osprey Optimization-Based Interpretable Deep Learning Framework for Predicting Coal Spontaneous Combustion Temperatures[J].Computers, Materials & Continua,2026,89(10):P.876-902,27.

基金项目

supported by the Basic Research Fund for Provincial Universities in Hebei Province(No.JJC2024082) （No.JJC2024082）

the Provincial College Student Innovation and Entrepreneurship Training Program(No.S202510081070). （No.S202510081070）

Computers, Materials & Continua

ISSN：1546-2218

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