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Hybrid Approach for Early Warning of Mine Water: Energy Density-Based Identification of Water-Conducting Channels Combined With Water Inflow Prediction by SA-LSTM.

, , , , , , , , and . IEEE Trans. Geosci. Remote. Sens., (2024)

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Combined machine-learning and optimization models for predicting carbon dioxide trapping indexes in deep geological formations., , , , and . Appl. Soft Comput., (August 2023)A Deep Learning-Based Data-Driven Approach for Predicting Mining Water Inrush From Coal Seam Floor Using Microseismic Monitoring Data., , , , , , and . IEEE Trans. Geosci. Remote. Sens., (2023)Hybrid Approach for Early Warning of Mine Water: Energy Density-Based Identification of Water-Conducting Channels Combined With Water Inflow Prediction by SA-LSTM., , , , , , , , and . IEEE Trans. Geosci. Remote. Sens., (2024)Evaluating the Applications of Dendritic Neuron Model with Metaheuristic Optimization Algorithms for Crude-Oil-Production Forecasting., , , , , and . Entropy, 24 (11): 1674 (November 2022)ARNS: A Data-Driven Approach for SoH Estimation of Lithium-Ion Battery Using Nested Sequence Models With Considering Relaxation Effect., , , , , , , , and . IEEE Access, (2022)Machine-learning predictions of solubility and residual trapping indexes of carbon dioxide from global geological storage sites., , , , , and . Expert Syst. Appl., (July 2023)Multi-Task with Variational Autoencoder for Lung Cancer Prognosis on Clinical Data., , , , , and . SMA, page 234-237. ACM, (2020)