Gas concentration prediction based on SSA algorithm with CNN-BiLSTM-attention

Accurate prediction of coal mine gas concentration is a crucial prerequisite for preventing gas exceed and disasters. However, the existing methods still suffer from issues such as low data utilization, difficulty in effectively integrating multivariate nonlinear spatiotemporal features, and poor ge...

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Veröffentlicht in:	Scientific reports Jg. 15; H. 1; S. 34214 - 13
Hauptverfasser:	Xing, Wenjing, Yang, Yanguo, Zhang, Yanxin, Yang, Yong
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	London Nature Publishing Group UK 01.10.2025 Nature Publishing Group Nature Portfolio
Schlagworte:	639/166 639/4077 639/705 704/172 Accuracy Algorithms Artificial intelligence Attention mechanism Coal mines Concentration prediction Deep learning Foraging behavior Forecasting Gas concentration Humanities and Social Sciences Integrated approach Machine learning Mining multidisciplinary Neural networks Occupational safety Optimization algorithms Predictions Science Science (multidisciplinary) Sparrow optimization algorithm Support vector machines Time series Wind speed Deep learning Sparrow optimization algorithm Attention mechanism Concentration prediction Gas concentration
ISSN:	2045-2322, 2045-2322
Online-Zugang:	Volltext
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