| A data-driven Bayesian network learning method for process fault diagnosis MT Amin, F Khan, S Ahmed, S Imtiaz Process Safety and Environmental Protection 150, 110-122, 2021 | 189 | 2021 |
| A bibliometric review and analysis of data-driven fault detection and diagnosis methods for process systems M Alauddin, F Khan, S Imtiaz, S Ahmed Industrial & Engineering Chemistry Research 57 (32), 10719-10735, 2018 | 163 | 2018 |
| Fault detection and pathway analysis using a dynamic Bayesian network MT Amin, F Khan, S Imtiaz Chemical Engineering Science 195, 777-790, 2019 | 154 | 2019 |
| Root cause diagnosis of process fault using KPCA and Bayesian network H Gharahbagheri, SA Imtiaz, F Khan Industrial & Engineering Chemistry Research 56 (8), 2054-2070, 2017 | 148 | 2017 |
| Human reliability assessment during offshore emergency conditions M Musharraf, J Hassan, F Khan, B Veitch, S MacKinnon, S Imtiaz Safety science 59, 19-27, 2013 | 144 | 2013 |
| Process System Fault Detection and Diagnosis Using a Hybrid Technique FK Amin, Md Tanjin, Syed Imtiaz Chemical Engineering Science, 2018 | 139 | 2018 |
| An analysis of process fault diagnosis methods from safety perspectives R Arunthavanathan, F Khan, S Ahmed, S Imtiaz Computers & Chemical Engineering 145, 107197, 2021 | 136 | 2021 |
| Dynamic availability assessment of safety critical systems using a dynamic Bayesian network MT Amin, F Khan, S Imtiaz Reliability Engineering & System Safety 178, 108-117, 2018 | 127 | 2018 |
| A deep learning model for process fault prognosis R Arunthavanathan, F Khan, S Ahmed, S Imtiaz Process Safety and Environmental Protection 154, 467-479, 2021 | 125 | 2021 |
| Treatment of missing values in process data analysis SA Imtiaz, SL Shah The Canadian Journal of Chemical Engineering 86 (5), 838-858, 2008 | 106 | 2008 |
| Risk-based fault detection and diagnosis for nonlinear and non-Gaussian process systems using R-vine copula MT Amin, F Khan, S Ahmed, S Imtiaz Process Safety and Environmental Protection 150, 123-136, 2021 | 87 | 2021 |
| Dynamic risk assessment and fault detection using principal component analysis O Zadakbar, S Imtiaz, F Khan Industrial & Engineering Chemistry Research 52 (2), 809-816, 2013 | 83 | 2013 |
| Copula-based Bayesian network model for process system risk assessment C Guo, F Khan, S Imtiaz Process Safety and Environmental Protection 123, 317-326, 2019 | 79 | 2019 |
| A novel data‐driven methodology for fault detection and dynamic risk assessment MT Amin, F Khan, S Ahmed, S Imtiaz The Canadian Journal of Chemical Engineering 98 (11), 2397-2416, 2020 | 78 | 2020 |
| Fault detection and diagnosis in process system using artificial intelligence-based cognitive technique R Arunthavanathan, F Khan, S Ahmed, S Imtiaz, R Rusli Computers & Chemical Engineering 134, 106697, 2020 | 76 | 2020 |
| A virtual experimental technique for data collection for a Bayesian network approach to human reliability analysis M Musharraf, D Bradbury-Squires, F Khan, B Veitch, S MacKinnon, ... Reliability Engineering & System Safety 132, 1-8, 2014 | 69 | 2014 |
| Review of interpretable machine learning for process industries A Carter, S Imtiaz, GF Naterer Process Safety and Environmental Protection 170, 647-659, 2023 | 53 | 2023 |
| Autonomous fault diagnosis and root cause analysis for the processing system using one-class SVM and NN permutation algorithm R Arunthavanathan, F Khan, S Ahmed, S Imtiaz Industrial & Engineering Chemistry Research 61 (3), 1408-1422, 2022 | 53 | 2022 |
| Dynamic risk assessment and fault detection using a multivariate technique O Zadakbar, S Imtiaz, F Khan Process Safety Progress 32 (4), 365-375, 2013 | 51 | 2013 |
| Robust process monitoring methodology for detection and diagnosis of unobservable faults MT Amin, F Khan, S Imtiaz, S Ahmed Industrial & Engineering Chemistry Research 58 (41), 19149-19165, 2019 | 48 | 2019 |
Faisal KhanTexas A&M University在 tamu.edu 的电子邮件经过验证