| Recurrent neural networks for short-term and long-term prediction of geothermal reservoirs A Jiang, Z Qin, D Faulder, TT Cladouhos, B Jafarpour Geothermics 104, 102439, 2022 | 9 | 2022 |
| A study on selecting optimum flash and evaporation temperatures for four geothermal power generation systems under different geofluid’s conditions Y Zhao, X Lu, J Zhu, W Zhang, K Hu, G Xin, F Jiang, Z Qin Energy Procedia 142, 439-446, 2017 | 8 | 2017 |
| A Multiscale Recurrent Neural Network Model for Long-Term Prediction of Geothermal Energy Production A Jiang, Z Qin, TT Cladouhos, D Faulder, B Jafarpour Stanford Geothermal Workshop, 2022 | 6 | 2022 |
| Recurrent Neural Networks for Prediction of Geothermal Reservoir Performance A Jiang, Z Qin, TT Cladouhos, D Faulder, B Jafarpour Stanford Geothermal Workshop, 2021 | 6 | 2021 |
| The lumped-parameter model on two-phase and superheated geothermal reservoir Z Qin, Á Valfells, MS Guðjónsdóttir Energy Procedia 142, 481-487, 2017 | 6 | 2017 |
| Efficient optimization of energy recovery from geothermal reservoirs with recurrent neural network predictive models Z Qin, A Jiang, D Faulder, TT Cladouhos, B Jafarpour Water Resources Research 59 (3), e2022WR032653, 2023 | 3 | 2023 |
| Physics-Guided Deep Learning for Prediction of Energy Production from Geothermal Reservoirs Z Qin, A Jiang, D Faulder, TT Cladouhos, B Jafarpour Geothermics 116, 102824, 2024 | 2 | 2024 |
| A multiscale recurrent neural network model for predicting energy production from geothermal reservoirs A Jiang, Z Qin, D Faulder, TT Cladouhos, B Jafarpour Geothermics 110, 102643, 2023 | 2 | 2023 |
| Physics-Guided Deep Learning for Prediction of Geothermal Reservoir Performance Z Qin, A Jiang, D Faulder, TT Cladouhos, B Jafarpour Stanford Geothermal Workshop, 2022 | 2* | 2022 |
Anyue JiangUniversity of Southern CaliforniaVerified email at usc.edu
