| 1 |
Estimating biofuel density via a soft computing approach based on intermolecular interactions
Nabipour N, Daneshfar R, Rezvanjou O, Mohammadi-Khanaposhtani M, Baghban A, Xiong QG, Li LKB, Habibzadeh S, Doranehgard MH
Renewable Energy, 152, 1086, 2020 |
| 2 |
Artificial neural network modeling and analysis of photovoltaic/thermal system based on the experimental study
Al-Waeli AHA, Sopian K, Yousif JH, Kazem HA, Boland J, Chaichan MT
Energy Conversion and Management, 186, 368, 2019 |
| 3 |
Determination of the Boyle temperature of pure gases using artificial neural networks
Coccia G, Di Nicola G, Tomassetti S, Pierantozzi M, Passerini G
Fluid Phase Equilibria, 493, 36, 2019 |
| 4 |
Development of a new multi-layer perceptron based soft sensor for SO2 emissions in power plant
Sun K, Wu XL, Xue JY, Ma FY
Journal of Process Control, 84, 182, 2019 |
| 5 |
Development of a new multi-layer perceptron based soft sensor for SO2 emissions in power plant
Sun K, Wu XL, Xue JY, Ma FY
Journal of Process Control, 84, 182, 2019 |
| 6 |
Predicting the water production of a solar seawater greenhouse desalination unit using multi-layer perceptron model
Zarei T, Behyad R
Solar Energy, 177, 595, 2019 |
| 7 |
Pipeline leak diagnosis based on wavelet and statistical features using Dempster-Shafer classifier fusion technique
Zadkarami M, Shahbazian M, Salahshoor K
Process Safety and Environmental Protection, 105, 156, 2017 |
| 8 |
Artificial neural network modeling of hydrogen-rich syngas production from methane dry reforming over novel Ni/CaFe2O4 catalysts
Hossain MA, Ayodele BV, Cheng CK, Khan MR
International Journal of Hydrogen Energy, 41(26), 11119, 2016 |
| 9 |
Pipeline leakage detection and isolation: An integrated approach of statistical and wavelet feature extraction with multi-layer perceptron neural network (MLPNN)
Zadkarami M, Shahbazian M, Salahshoor K
Journal of Loss Prevention in The Process Industries, 43, 479, 2016 |
| 10 |
Most influential parametrical and data needs for realistic wind speed prediction
Agrawal A, Sandhu KS
Renewable Energy, 94, 452, 2016 |
