Deep Learning in Energy Production

wind

This blog post has recent publications about use of Deep Learning in Energy Production context (wind, gas and oil), e.g. wind power prediction, turbine risk assessment, reservoir discovery and price forecasting.

Best regards,

Amund Tveit

Wind

Year  Title Author
2017 Short-term Wind Energy Prediction Algorithm Based on SAGA-DBNs  W Fei, WU Zhong
2017 Wind Power Prediction using Deep Neural Network based Meta Regression and Transfer Learning  AS Qureshi, A Khan, A Zameer, A Usman
2017 Wind Turbine Failure Risk Assessment Model Based on DBN  C Fei, F Zhongguang
2017 The optimization of wind power interval forecast  X Yu, H Zang
2016 Deep Learning for Wind Speed Forecasting in Northeastern Region of Brazil  AT Sergio, TB Ludermir
2016 A very short term wind power prediction approach based on Multilayer Restricted Boltzmann Machine  X Peng, L Xiong, J Wen, Y Xu, W Fan, S Feng, B Wang
2016 Short-term prediction of wind power based on deep Long Short-Term Memory  Q Xiaoyun, K Xiaoning, Z Chao, J Shuai, M Xiuda
2016 Deep belief network based deterministic and probabilistic wind speed forecasting approach  HZ Wang, GB Wang, GQ Li, JC Peng, YT Liu
2016 A hybrid wind power prediction method  Y Tao, H Chen
2016 Deep learning based ensemble approach for probabilistic wind power forecasting  H Wang, G Li, G Wang, J Peng, H Jiang, Y Liu
2016 A hybrid wind power forecasting model based on data mining and wavelets analysis  R Azimi, M Ghofrani, M Ghayekhloo
2016 ELM Based Representational Learning for Fault Diagnosis of Wind Turbine Equipment  Z Yang, X Wang, PK Wong, J Zhong
2015 Deep Neural Networks for Wind Energy Prediction  D Díaz, A Torres, JR Dorronsoro
2015 Predictive Deep Boltzmann Machine for Multiperiod Wind Speed Forecasting  CY Zhang, CLP Chen, M Gan, L Chen
2015 Resilient Propagation for Multivariate Wind Power Prediction  J Stubbemann, NA Treiber, O Kramer
2015 Transfer learning for short-term wind speed prediction with deep neural networks  Q Hu, R Zhang, Y Zhou
2014 Wind Power Prediction and Pattern Feature Based on Deep Learning Method  Y Tao, H Chen, C Qiu

Gas

Year  Title Author
2017   Sample Document–Inversion Of The Permeability Of A Tight Gas Reservoir With The Combination Of A Deep Boltzmann Kernel …  L Zhu, C Zhang, Y Wei, X Zhou, Y Huang, C Zhang
2017   Deep Learning: Chance and Challenge for Deep Gas Reservoir Identification  C Junxing, W Shikai
2016   Finite-sensor fault-diagnosis simulation study of gas turbine engine using information entropy and deep belief networks  D Feng, M Xiao, Y Liu, H Song, Z Yang, Z Hu
2015   On Accurate and Reliable Anomaly Detection for Gas Turbine Combustors: A Deep Learning Approach  W Yan, L Yu
2015   A Review of Datasets and Load Forecasting Techniques for Smart Natural Gas and Water Grids: Analysis and Experiments.  M Fagiani, S Squartini, L Gabrielli, S Spinsante
2015   Short-term load forecasting for smart water and gas grids: A comparative evaluation  M Fagiani, S Squartini, R Bonfigli, F Piazza
2015   The early-warning model of equipment chain in gas pipeline based on DNN-HMM  J Qiu, W Liang, X Yu, M Zhang, L Zhang

Oil

Year  Title Author
2017   Development of a New Correlation for Bubble Point Pressure in Oil Reservoirs Using Artificial Intelligent Technique  S Elkatatny, M Mahmoud
2017   A deep learning ensemble approach for crude oil price forecasting  Y Zhao, J Li, L Yu
2016   Automatic Detection and Classification of Oil Tanks in Optical Satellite Images Based on Convolutional Neural Network  Q Wang, J Zhang, X Hu, Y Wang
2015   A Hierarchical Oil Tank Detector With Deep Surrounding Features for High-Resolution Optical Satellite Imagery  L Zhang, Z Shi, J Wu

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