Items where Author is "Taqvi, S.A.A."

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Number of items: 15.

Article

Taqvi, S.A.A. and Zabiri, H. and Singh, S.K.M. and Tufa, L.D. and Naqvi, M. (2023) Investigation of control performance on an absorption/stripping system to remove CO2 achieving clean energy systems. Fuel, 347. ISSN 00162361

Asif, K. and Lock, S.S.M. and Taqvi, S.A.A. and Jusoh, N. and Yiin, C.L. and Chin, B.L.F. (2023) A molecular simulation study on amine-functionalized silica/polysulfone mixed matrix membrane for mixed gas separation. Chemosphere, 311.

Kok, T.L. and Aldrich, C. and Zabiri, H. and Taqvi, S.A.A. and Olivier, J. (2022) Application of unthresholded recurrence plots and texture analysis for industrial loops with faulty valves. Soft Computing.

kazmi , B. and Taqvi, S.A.A. and Naqvi, M. and Ilyas, S.U. and Moshin, A. and Inamullah, F. and Naqvi, S.R. (2022) Correction to: Process system analysis on oil processing facility and economic viability from oil well�to�tank (SN Applied Sciences, (2021), 3, 7, (682), 10.1007/s42452-021-04635-z). SN Applied Sciences, 4 (2).

kazmi, B. and Taqvi, S.A.A. and Naqvi, M. and Ilyas, S.U. and Moshin, A. and Inamullah, F. and Naqvi, S.R. (2022) Correction to: Process system analysis on oil processing facility and economic viability from oil well�to�tank (SN Applied Sciences, (2021), 3, 7, (682), 10.1007/s42452-021-04635-z). SN Applied Sciences, 4 (2). ISSN 25233971

Arshad, U. and Taqvi, S.A.A. and Buang, A. (2022) Experimental analysis and data-driven machine learning modelling of the minimum ignition temperature (MIT) of aluminium dust. Fuel, 324.

Arshad, U. and Taqvi, S.A.A. and Buang, A. (2022) Experimental analysis and data-driven machine learning modelling of the minimum ignition temperature (MIT) of aluminium dust. Fuel, 324.

Fatima, S.A. and Zabiri, H. and Taqvi, S.A.A. and Ramli, N. and Maulud, A.S. (2022) Intelligent Control of an Industrial Debutanizer Column. Chemical Engineering and Technology.

Taqvi, S.A.A. and Zabiri, H. and Uddin, F. and Naqvi, M. and Tufa, L.D. and Kazmi, M. and Rubab, S. and Naqvi, S.R. and Maulud, A.S. (2022) Simultaneous fault diagnosis based on multiple kernel support vector machine in nonlinear dynamic distillation column. Energy Science and Engineering, 10 (3). pp. 814-839.

Arshad, U. and Taqvi, S.A.A. and Buang, A. (2021) Modelling of the minimum ignition temperature (MIT) of corn dust using statistical analysis and artificial neural networks based on the synergistic effect of concentration and dispersion pressure. Process Safety and Environmental Protection, 147. pp. 742-755.

kazmi , B. and Taqvi, S.A.A. and Naqvi, M. and Ilyas, S.U. and Moshin, A. and Inamullah, F. and Naqvi, S.R. (2021) Process system analysis on oil processing facility and economic viability from oil well-to-tank. SN Applied Sciences, 3 (7).

Taqvi, S.A.A. and Zabiri, H. and Tufa, L.D. and Uddin, F. and Fatima, S.A. and Maulud, A.S. (2021) A Review on Data-Driven Learning Approaches for Fault Detection and Diagnosis in Chemical Processes. ChemBioEng Reviews, 8 (3). pp. 239-259.

Arshad, U. and Taqvi, S.A.A. and Buang, A. and Awad, A. (2021) SVM, ANN, and PSF modelling approaches for prediction of iron dust minimum ignition temperature (MIT) based on the synergistic effect of dispersion pressure and concentration. Process Safety and Environmental Protection, 152. pp. 375-390.

Zulfiqar, M. and Samsudin, M.F.R. and Taqvi, S.A.A. and Sufian, S. (2020) Corrigendum to �Modelling and optimization of photocatalytic degradation of phenol via TiO2 nanoparticles: An insight into response surface methodology and artificial neural network� J. Photochem. Photobiol. A: Chem. 384 (2019) 1�15/112039 (Journal of Photochemistry & Photobiology, A: Chemistry (2019) 384, (S1010603019308883), (10.1016/j.jphotochem.2019.112039)). Journal of Photochemistry and Photobiology A: Chemistry, 400.

Taqvi, S.A.A. and Zabiri, H. and Tufa, L.D. and Uddin, F. and Fatima, S.A. and Maulud, A.S. (2020) Narx network based data-driven algorithm for detection of tray faults in nonlinear dynamic distillation column. Jurnal Teknologi, 82 (5). pp. 43-50.

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