| Dynamic kriging based fault detection and diagnosis approach for nonlinear noisy dynamic processes A Shokry, MH Ardakani, G Escudero, M Graells, A Espuña Computers & Chemical Engineering 106, 758-776, 2017 | 17 | 2017 |
| Optimal features selection for designing a fault diagnosis system M Ardakani, M Askarian, A Shokry, G Escudero, M Graells, A Espuña Computer Aided Chemical Engineering 38, 1111-1116, 2016 | 17 | 2016 |
| Imputation of missing data with ordinary kriging for enhancing fault detection and diagnosis M Ardakani, A Shokry, G Saki, G Escudero, M Graells, A Espuña Computer Aided Chemical Engineering 38, 1377-1382, 2016 | 8 | 2016 |
| Kriging based fault detection and diagnosis approach for nonlinear noisy dynamic processes A Shokry, M Ardakani, G Escudero, M Graells, A Espuña Computer Aided Chemical Engineering 38, 55-60, 2016 | 6 | 2016 |
| Incremental learning fault detection algorithm based on hyperplane-distance M Ardakani, G Escudero, M Graells, A Espuña Computer Aided Chemical Engineering 38, 1105-1110, 2016 | 5 | 2016 |
| OPTIMIZATION AND KINETIC EVALUATION OF ACID BLUE193 DEGRADATION BY UV/PEROXYDISULFATE OXIDATION USING RESPONSE SURFACE METHODOLOGY M Ahmadi, MH Ardakani, ALA Zinatizadeh ADVANCES IN ENVIRONMENTAL TECHNOLOGY 1 (2), 59-68, 2015 | 5 | 2015 |
| A framework for unsupervised fault detection and diagnosis based on clustering assisted kriging observer MH Ardakani, A Shokry, G Escudero, M Graells, A Espuña 2016 3rd Conference on Control and Fault-Tolerant Systems (SysTol), 183-188, 2016 | 4 | 2016 |
| Unsupervised automatic updating of classification models of fault diagnosis for novelty detection MH Ardakani, A Shokry, G Escudero, M Graells, A Espuña Computer Aided Chemical Engineering 43, 1123-1128, 2018 | 3 | 2018 |
| Toward online explore of concept drift for fault detection of chemical processes MH Ardakani, M Askarian, G Escudero, M Graells, A Espuna Computer Aided Chemical Engineering 40, 1657-1662, 2017 | 3 | 2017 |
| Online quantification of the concept drift using incremental learned classifier and non-automatic clustering MH Ardakani, A Shokry, G Escudero, M Graells, A Espuña Computer Aided Chemical Engineering 43, 1069-1074, 2018 | 2 | 2018 |
| Sliding dynamic data window: Improving properties of the incremental learning methods MH Ardakani, G Escudero, M Graells, A Espuña Computer Aided Chemical Engineering 40, 1663-1668, 2017 | 2 | 2017 |
| Data Driven Process Monitoring, from Fault Detection and Diagnosis Points of View, in Industry 4.0 Context H Ardakani, H Hemmati, MR Hernandez Computer Aided Chemical Engineering 51, 1033-1038, 2022 | | 2022 |
| Fault diagnosis using the incremental learning algorithm with support vector machine MH Ardakani, M Graells Sobré, G Escudero Bakx ECCE 10+ ECAB 3+ EPIC 5: 10th European Congress of Chemical Engineering …, 2015 | | 2015 |
Moisès GraellsAssociate Professor, Chemical Engineering Department, Universitat Politècnica de CatalunyaVerified email at upc.edu
