| An adaptive inertia weight teaching-learning-based optimization algorithm and its applications AK Shukla, P Singh, M Vardhan Applied Mathematical Modelling 77, 309-326, 2020 | 110 | 2020 |
| A new hybrid wrapper TLBO and SA with SVM approach for gene expression data AK Shukla, P Singh, M Vardhan Information Sciences 503, 238-254, 2019 | 87 | 2019 |
| two-stage gene selection method for biomarker discovery from microarray data for cancer classification AK Shukla, P Singh, M Vardhan Chemometrics and Intelligent Laboratory Systems 183, 47-58, 2018 | 68 | 2018 |
| A hybrid gene selection method for microarray recognition AK Shukla, P Singh, M Vardhan Biocybernetics and Biomedical Engineering 38 (4), 975-991, 2018 | 68 | 2018 |
| Gene selection for cancer types classification using novel hybrid metaheuristics approach AK Shukla, P Singh, M Vardhan Swarm and Evolutionary Computation 54, 100661, 2020 | 66 | 2020 |
| A new hybrid feature subset selection framework based on binary genetic algorithm and information theory AK Shukla, P Singh, M Vardhan International Journal of Computational Intelligence and Applications 18 (03 …, 2019 | 60 | 2019 |
| Implementation of adaptive scheme in evolutionary technique for anomaly-based intrusion detection S Dwivedi, M Vardhan, S Tripathi, AK Shukla Evolutionary intelligence 13 (1), 103-117, 2020 | 58 | 2020 |
| A study on metaheuristics approaches for gene selection in microarray data: algorithms, applications and open challenges AK Shukla, D Tripathi, BR Reddy, D Chandramohan Evolutionary intelligence 13 (3), 309-329, 2020 | 56 | 2020 |
| An empirical evaluation of teaching–learning-based optimization, genetic algorithm and particle swarm optimization AK Shukla, SK Pippal, SS Chauhan International Journal of Computers and Applications 45 (1), 36-50, 2023 | 36 | 2023 |
| Detection of anomaly intrusion utilizing self-adaptive grasshopper optimization algorithm AK Shukla Neural Computing and Applications 33 (13), 7541-7561, 2021 | 35 | 2021 |
| Detecting biomarkers from microarray data using distributed correlation based gene selection AK Shukla, D Tripathi Genes & Genomics, 1-17, 2020 | 35 | 2020 |
| Identification of potential biomarkers on microarray data using distributed gene selection approach AK Shukla, D Tripathi Mathematical biosciences 315, 108230, 2019 | 35 | 2019 |
| Preparedness among dental professionals towards COVID-19 in India KT Singh, G Mishra, AK Shukla, S Behera, AK Tiwari, S Panigrahi, ... Pan African Medical Journal 36 (1), 2020 | 32 | 2020 |
| Multi-population adaptive genetic algorithm for selection of microarray biomarkers AK Shukla Neural Computing and Applications, 1-22, 2020 | 31 | 2020 |
| A hybrid framework for optimal feature subset selection AK Shukla, P Singh, M Vardhan Journal of Intelligent & Fuzzy Systems 36 (3), 2247-2259, 2019 | 30 | 2019 |
| Credit scoring models using ensemble learning and classification approaches: a comprehensive survey D Tripathi, AK Shukla, BR Reddy, GS Bopche, D Chandramohan Wireless Personal Communications 123 (1), 785-812, 2022 | 29 | 2022 |
| Experimental analysis of machine learning methods for credit score classification D Tripathi, DR Edla, A Bablani, AK Shukla, BR Reddy Progress in Artificial Intelligence 10 (3), 217-243, 2021 | 28 | 2021 |
| Building an effective approach toward intrusion detection using ensemble feature selection AK Shukla, P Singh International Journal of Information Security and Privacy (IJISP) 13 (3), 31-47, 2019 | 28 | 2019 |
| Identification of cancerous gene groups from microarray data by employing adaptive genetic and support vector machine technique AK Shukla Computational Intelligence, 2019 | 25 | 2019 |
| Neighbour teaching learning based optimization for global optimization problems AK Shukla, P Singh, M Vardhan Journal of Intelligent & Fuzzy Systems 34 (3), 1583-1594, 2018 | 20 | 2018 |
