| 1 |
A novel rate of penetration prediction model with identified condition for the complex geological drilling process
Zhou Y, Chen X, Zhao HB, Wu M, Cao WH, Zhang YC, Liu HB
Journal of Process Control, 100, 30, 2021 |
| 2 |
Development and analyses of data-driven models for predicting the bed depth profile of solids flowing in a rotary kiln
Parveen N, Zaidi S, Danish M
Advanced Powder Technology, 31(2), 678, 2020 |
| 3 |
Artificial intelligence (AI)-based friction factor models for large piping networks
Parveen N, Zaidi S, Danish M
Chemical Engineering Communications, 207(2), 213, 2020 |
| 4 |
Support vector regression: A novel soft computing technique for predicting the removal of cadmium from wastewater
Parveen N, Zaidi S, Danish M
Indian Journal of Chemical Technology, 27(1), 43, 2020 |
| 5 |
Operation planning method for home air-conditioners considering characteristics of installation environment
Kuroha R, Fujimoto Y, Hirohashi W, Amano Y, Tanabe S, Hayashi Y
Energy and Buildings, 177, 351, 2018 |
| 6 |
An improved variable selection method for support vector regression in NIR spectral modeling
Xu S, Lu B, Baldea M, Edgar TF, Nixon M
Journal of Process Control, 67, 83, 2018 |
| 7 |
Development of SVR-based model and comparative analysis with MLR and ANN models for predicting the sorption capacity of Cr(VI)
Parveen N, Zaidi S, Danish M
Process Safety and Environmental Protection, 107, 428, 2017 |
| 8 |
Estimation of the building energy use intensity in the urban scale by integrating GIS and big data technology
Ma J, Cheng JCP
Applied Energy, 183, 182, 2016 |
| 9 |
Application of support vector machine in QSAR study of triazolyl thiophenes as cyclin dependent kinase-5 inhibitors for their anti-alzheimer activity
Garkani-Nejad Z, Ghanbari A
Indian Journal of Chemical Technology, 23(1), 9, 2016 |
| 10 |
An improved support vector regression model for estimation of saturation pressure of crude oils
Ansari HR, Gholami A
Fluid Phase Equilibria, 402, 124, 2015 |
