Machine learning in the identification, prediction and exploration of environmental toxicology: Challenges and perspectives
X Wu, Q Zhou, L Mu, X Hu - Journal of Hazardous Materials, 2022 - Elsevier
Over the past few decades, data-driven machine learning (ML) has distinguished itself from
hypothesis-driven studies and has recently received much attention in environmental …
hypothesis-driven studies and has recently received much attention in environmental …
Dimensionality reduction in surrogate modeling: A review of combined methods
CKJ Hou, K Behdinan - Data Science and Engineering, 2022 - Springer
Surrogate modeling has been popularized as an alternative to full-scale models in complex
engineering processes such as manufacturing and computer-assisted engineering. The …
engineering processes such as manufacturing and computer-assisted engineering. The …
Real-time natural gas release forecasting by using physics-guided deep learning probability model
Natural gas release from oil and gas facilities contributes significantly to the greenhouse
effect and reduces the benefit of displacing heavy fossil fuels with natural gas. Real-time …
effect and reduces the benefit of displacing heavy fossil fuels with natural gas. Real-time …
Detecting respiratory pathologies using convolutional neural networks and variational autoencoders for unbalancing data
MT García-Ordás, JA Benítez-Andrades… - Sensors, 2020 - mdpi.com
The aim of this paper was the detection of pathologies through respiratory sounds. The
ICBHI (International Conference on Biomedical and Health Informatics) Benchmark was …
ICBHI (International Conference on Biomedical and Health Informatics) Benchmark was …
Deep neural network-based optimization framework for safety evacuation route during toxic gas leak incidents
Evacuation planning is important for reducing casualties in toxic gas leak incidents.
However, most evacuation plans are too qualitative to be applied to unexpected practical …
However, most evacuation plans are too qualitative to be applied to unexpected practical …
A novel semi-supervised pre-training strategy for deep networks and its application for quality variable prediction in industrial processes
Deep learning-based soft sensor has been a hot topic for quality variable prediction in
modern industrial processes. Feature representation with deep learning is the key step to …
modern industrial processes. Feature representation with deep learning is the key step to …
Real-time hydrogen release and dispersion modelling of hydrogen refuelling station by using deep learning probability approach
Hydrogen release and dispersion from hydrogen refuelling stations have the potential to
cause explosion disaster and bring significant causalities and economic losses to the …
cause explosion disaster and bring significant causalities and economic losses to the …
Real-time plume tracking using transfer learning approach
Deep learning has been used to track the real-time flammable plume of natural gas.
However, a large volume of high-fidelity data is required to train the deep learning model for …
However, a large volume of high-fidelity data is required to train the deep learning model for …
Prediction model for the evolution of hydrogen concentration under leakage in hydrogen refueling station using deep neural networks
X He, D Kong, X Yu, P Ping, G Wang, R Peng… - International Journal of …, 2024 - Elsevier
The widespread risks of leakages in the hydrogen industry chain require a method that can
quickly predict the consequences of accidents, especially in the hydrogen refueling station …
quickly predict the consequences of accidents, especially in the hydrogen refueling station …
A review of advances towards efficient reduced-order models (ROM) for predicting urban airflow and pollutant dispersion
Computational fluid dynamics (CFD) models have been used for the simulation of urban
airflow and pollutant dispersion, due to their capability to capture different length scales and …
airflow and pollutant dispersion, due to their capability to capture different length scales and …