| An efficient unsupervised feature selection procedure through feature clustering X Yan, S Nazmi, BA Erol, A Homaifar, B Gebru, E Tunstel Pattern Recognition Letters 131, 277-284, 2020 | 41 | 2020 |
| Evolving multi-label classification rules by exploiting high-order label correlations S Nazmi, X Yan, A Homaifar, E Doucette Neurocomputing 417, 176-186, 2020 | 21 | 2020 |
| A novel clustering algorithm based on fitness proportionate sharing X Yan, A Homaifar, S Nazmi, M Razeghi-Jahromi 2017 IEEE International Conference on Systems, Man, and Cybernetics (SMC …, 2017 | 15 | 2017 |
| A clustering-based active learning method to query informative and representative samples X Yan, S Nazmi, B Gebru, M Anwar, A Homaifar, M Sarkar, KD Gupta Applied Intelligence 52 (11), 13250-13267, 2022 | 12 | 2022 |
| Multi-label classification using genetic-based machine learning S Nazmi, X Yan, A Homaifar 2018 IEEE International Conference on Systems, Man, and Cybernetics (SMC …, 2018 | 7 | 2018 |
| Multilabel classification with weighted labels using learning classifier systems S Nazmi, M Razeghi-Jahromi, A Homaifar 2017 16th IEEE International Conference on Machine Learning and Applications …, 2017 | 7 | 2017 |
| Multi-label classification with local pairwise and high-order label correlations using graph partitioning S Nazmi, X Yan, A Homaifar, M Anwar Knowledge-Based Systems 233, 107414, 2021 | 6 | 2021 |
| An evidence theory based multi sensor data fusion for multiclass classification G Awogbami, N Agana, S Nazmi, X Yan, A Homaifar 2018 IEEE International Conference on Systems, Man, and Cybernetics (SMC …, 2018 | 5 | 2018 |
| A supervised feature selection method for mixed-type data using density-based feature clustering X Yan, M Sarkar, B Gebru, S Nazmi, A Homaifar 2021 IEEE International Conference on Systems, Man, and Cybernetics (SMC …, 2021 | 4 | 2021 |
| A new combination rule based on the average belief function G Awogbami, N Agana, S Nazmi, A Homaifar SoutheastCon 2018, 1-5, 2018 | 4 | 2018 |
| Functional observer design with application to pre-compensated multi-variable systems S Nazmi, R Mohajerpoor, H Abdi, S Nahavandi 2015 IEEE Conference on Control Applications (CCA), 620-625, 2015 | 4 | 2015 |
| A Software Tool for Evaluating Unmanned Autonomous Systems SN Abdollah Homaifar, Ali Karimoddini, Mike Heiges, Mubbashar A. Khan, Berat ... International Journal of Test & Evaluation 41 (3), 188-195, 2020 | 3* | 2020 |
| Determination of the Driver At-fault Using Possibility Theory-based Classification S Nazmi, S Ramyar, A Homaifar Transportation Research Board Annual Meeting 2019, 2019 | 3 | 2019 |
| Possibility rule-based classification using function approximation S Nazmi, A Homaifar 2018 IEEE International Conference on Systems, Man, and Cybernetics (SMC …, 2018 | 3 | 2018 |
| Mitigating shortage of labeled data using clustering-based active learning with diversity exploration X Yan, S Nazmi, B Gebru, M Anwar, A Homaifar, M Sarkar, KD Gupta arXiv preprint arXiv:2207.02964, 2022 | 2 | 2022 |
| An effective action covering for multi-label learning classifier systems: a graph-theoretic approach S Nazmi, A Homaifar, M Anwar Proceedings of the Genetic and Evolutionary Computation Conference, 340-348, 2021 | 2 | 2021 |
| A Rule-Based Evolutionary Approach to Multi-Label Classification S Nazmi North Carolina Agricultural and Technical State University, 2021 | | 2021 |
| Two-Step Markov Update Algorithm for Accuracy-Based Learning Classifier Systems. M Razeghi-Jahromi, S Nazmi, A Homaifar Complex Systems 27 (1), 2018 | | 2018 |
Abdollah HomaifarProfessor of Electrical Engineering, North Carolina A&T State UniversityVerified email at ncat.edu
