S. S. Pradhan and S. Panigrahi,"Studies on machine learning techniques for multivariate forecasting of Delhi air quality index", in Advances in Data-Driven Computing and Intelligent Systems. ADCIS 2022., vol.698, pp.133–146, Springer, August 2023, 10.1007/978-981-99-3250-4_10       Inproceedings

S. S. Pradhan, S. Panigrahi, S. K. Purohit, and J. K. Dash,"Study and development of hybrid and ensemble forecasting models for air quality index forecasting", Expert Syatems, Wiley, September 2023, 10.1111/exsy.13449       Article

G. Shial, S. Sahoo, and S. Panigrahi,"A NATURE-INSPIRED HYBRID PARTITIONAL CLUSTERING METHOD BASED ON GREY WOLF OPTIMIZATION AND JAYA ALGORITHM", Computer Science, vol.24, no.3, pp.355-399, October 2023, 10.7494/csci.2023.24.3.4962       Article

M. K. Kar, S. Kumar, A. K. Singh, S. Panigrahi, and M. Cherukuri,"Design and analysis of FOPID-Based damping controllers using a modified grey wolf optimization algorithm", International Transactions on Electrical Energy Systems, pp.1-31, Hindawi 2022, 10.1155/2022/5339630       Article

R. Yelchuri, J. K. Dash, P. Singh, A. Mahapatro, and S. Panigrahi,"Exploiting deep and hand-crafted features for texture image retrieval using class membership", Pattern Recognition Letters, vol.160, pp.163-171, Elsevier 2022, 10.1016/j.patrec.2022.06.017       Article

R. Pradhan, S. Panigrahi, and P. K. Sahu,"Implementation of gradient gravitational search algorithm towards conformational search", Computational and Theoretical Chemistry, vol.1208, pp.113550, Elsevier 2022, 10.1016/j.comptc.2021.113550       Article

G. Shial, S. Sahoo, and S. Panigrahi,"Identification and analysis of breast cancer disease using swarm and evolutionary algorithm", in 2022 IEEE Region 10 Symposium (TENSYMP), pp.1-6, IEEE, Mumbai, India 2022, 10.1109/TENSYMP54529.2022.9864514       Inproceedings

G. Shial, S. Sahoo, and S. Panigrahi,"Community detection and disease identification using meta-heuristic based clustering methods", in 2022 IEEE India Council International Subsections Conference (INDISCON), pp.1-6, IEEE, Bhubaneswar, India 2022, 10.1109/INDISCON54605.2022.9862931       Inproceedings

R., H., and S. Panigrahi,"A novel probabilistic intuitionistic fuzzy set based model for high order fuzzy time series forecasting", Engineering Applications of Artificial Intelligence, vol.99, pp.104136, Elsevier 2021, 10.1016/j.engappai.2020.104136       Article

R., H. Behera, and S. Panigrahi,"A non-probabilistic neutrosophic entropy-based method for high-order fuzzy time series forecasting", Arabian Journal for Science and Engineering, vol.47, no.2, pp.1399-1421, Springer 2021, 10.1007/s13369-021-05718-0       Article