| 1 |
Advanced intelligence frameworks for predicting maximum pitting corrosion depth in oil and gas pipelines
Ben Seghier ME, Keshtegar B, Taleb-Berrouane M, Abbassi R, Trung NT
Process Safety and Environmental Protection, 147, 818, 2021 |
| 2 |
Artificial intelligence (AI)-based friction factor models for large piping networks
Parveen N, Zaidi S, Danish M
Chemical Engineering Communications, 207(2), 213, 2020 |
| 3 |
Artificial intelligence implementation framework development for building energy saving
Lee DS, Huang HY, Lee WS, Liu YH
International Journal of Energy Research, 44(14), 11908, 2020 |
| 4 |
Prospect for small-hydropower installation settled upon optimal water allocation: An action to stimulate synergies of water-food-energy nexus
Zhou YL, Chang LC, Uen TS, Guo SL, Xu CY, Chang FJ
Applied Energy, 238, 668, 2019 |
| 5 |
A new generation of AI: A review and perspective on machine learning technologies applied to smart energy and electric power systems
Cheng LF, Yu T
International Journal of Energy Research, 43(6), 1928, 2019 |
| 6 |
An evaluation of machine learning and artificial intelligence models for predicting the flotation behavior of fine high-ash coal
Ali D, Hayat MB, Alagha L, Molatlhegi OK
Advanced Powder Technology, 29(12), 3493, 2018 |
| 7 |
Agile Program Management for Chemical Engineering and the IoT
Sato T
Journal of Chemical Engineering of Japan, 51(9), 826, 2018 |
