Energy consumption of intermittent ventilation strategies of different air distribution modes for indoor pollutant removal

Z Cao, Y An, Y Wang, Y Bai, T Zhao, C Zhai - Journal of Building …, 2023 - Elsevier
Efficient ventilation methods and ventilation strategies are required to improve the energy
savings of the ventilation systems of industrial plants. This study investigated the energy …

Review on machine learning-based underground coal mines gas hazard identification and estimation techniques

M Sharma, T Maity - Archives of Computational Methods in Engineering, 2024 - Springer
The underground coal mines (UCM) exhibit many life-threatening hazards for mining
workers. In contrast, gas hazards are among the most critical challenges to handle. This …

Air cargo transport demand forecasting using ConvLSTM2D, an artificial neural network architecture approach

JGM Anguita, OD Olariaga - Case Studies on Transport Policy, 2023 - Elsevier
The prediction of air traffic demand (passengers and cargo) in a regional/national air
transport system is essential. Knowing the behavior of future demand helps, on the one …

Unified CNN-LSTM for keyhole status prediction in PAW based on spatial-temporal features

F Zhou, X Liu, C Jia, S Li, J Tian, W Zhou… - Expert Systems with …, 2024 - Elsevier
Despite the high efficiency of keyhole plasma arc welding (K-PAW), it still has several
deficiencies, such as narrow welding parameter ranges, easily disturbed welding process …

A hybrid deep leaning model for prediction and parametric sensitivity analysis of noise annoyance

SK Tiwari, LA Kumaraswamidhas, Prince… - … Science and Pollution …, 2023 - Springer
Noise annoyance is recognized as an expression of physiological and psychological strain
in acoustical environment. The studies on prediction of noise annoyance and parametric …

Ensemble water quality forecasting based on decomposition, sub-model selection, and adaptive interval

T Liu, W Liu, Z Liu, H Zhang, W Liu - Environmental Research, 2023 - Elsevier
The prediction of effluent quality for wastewater treatment plants (WWTPs) has caused
widespread concern due to its essential role in ensuring water quality standards and …

Residual-aware deep attention graph convolutional network via unveiling data latent interactions for product quality prediction in industrial processes

Y Chen, Y Wang, Q Sui, X Yuan, K Wang… - Expert Systems with …, 2024 - Elsevier
Data-driven modeling based on deep learning is crucial for online product quality prediction
in industrial processes. Extracting latent data interactions from sensor variables lies at the …

Neural network models and shapley additive explanations for a beam-ring structure

Y Sun, L Zhang, M Yao, J Zhang - Chaos, Solitons & Fractals, 2024 - Elsevier
A combination of neural network modeling, SHapley Additive exPlanations (SHAP) and
model simplification is proposed and applied to the system of a beam-ring structure in this …

A hybrid forecasting architecture for air passenger demand considering search engine data and spatial effect

X Liang, C Hong, J Chen, Y Wang, M Yang - Journal of Air Transport …, 2024 - Elsevier
As the global process of digitalization accelerates and breakthroughs in internet technology
emerge, governments worldwide are advocating for data-driven decision-making, aiming to …

An intelligent airflow perception model for metal mines based on CNN-LSTM architecture

W Tang, Q Zhang, Y Chen, X Liu, H Wang… - Process Safety and …, 2024 - Elsevier
In view of the harsh underground working environment and difficulties of airflow monitoring
sensors placement, implementing an intelligent ventilation strategy is crucial for ensuring …