| 1 |
Development of deep learning-based equipment heat load detection for energy demand estimation and investigation of the impact of illumination
Wei SY, Calautit J
International Journal of Energy Research, 45(5), 7204, 2021 |
| 2 |
Spatio-temporal fusion neural network for multi-class fault diagnosis of wind turbines based on SCADA data
Pang YH, He Q, Jiang GQ, Xie P
Renewable Energy, 161, 510, 2020 |
| 3 |
CNN-PFVS: Integrating Neural Network and Finite Volume Models to Accelerate Flow Simulation on Pore Space Images
Chung T, Wang YD, Armstrong RT, Mostaghimi P
Transport in Porous Media, 135(1), 25, 2020 |
| 4 |
A novel deep learning method for the classification of power quality disturbances using deep convolutional neural network
Wang SX, Chen HW
Applied Energy, 235, 1126, 2019 |
| 5 |
Measuring Particle Size Distributions in Multiphase Flows Using a Convolutional Neural Network
Schafer J, Schmitt P, Hlawitschka MW, Bart HJ
Chemie Ingenieur Technik, 91(11), 1688, 2019 |
| 6 |
Fault diagnosis for distillation process based on CNN-DAE
Li CK, Zhao DF, Mu SJ, Zhang WH, Shi N, Li LN
Chinese Journal of Chemical Engineering, 27(3), 598, 2019 |
| 7 |
Short-term load forecasting by using a combined method of convolutional neural networks and fuzzy time series
Sadaei HJ, Silva PCDE, Guimaraes FG, Lee MH
Energy, 175, 365, 2019 |
| 8 |
Generative adversarial networks and convolutional neural networks based weather classification model for day ahead short-term photovoltaic power forecasting
Wang F, Zhang ZY, Liu C, Yu YL, Pang SL, Duic N, Shafie-Khah M, Catalao JPS
Energy Conversion and Management, 181, 443, 2019 |
| 9 |
Automatic detection of the onset of film boiling using convolutional neural networks and Bayesian statistics
Hobold GM, da Silva AK
International Journal of Heat and Mass Transfer, 134, 262, 2019 |
| 10 |
Flotation froth image recognition with convolutional neural networks
Fu Y, Aldrich C
Minerals Engineering, 132, 183, 2019 |
