S. K. Purohit and S. Panigrahi,"Novel deterministic and probabilistic forecasting methods for crude oil price employing optimized deep learning, statistical and hybrid models", Information Sciences, vol.658, pp.120021, Elsevier, February 2024, 10.1016/j.ins.2023.120021       Article

A. P. Padhy, S. Panigrahi, V. P. Singh, and P. Pratyasha,"Model order reduction for SISO and MIMO system using improved adaptive differential evolution algorithm", Soft Computing, Springer, January 2024, 10.1007/s00500-023-09489-8       Article

S. K. Purohit and S. Panigrahi,"Forecasting Crude Oil Prices: A Machine Learning Perspective", in International Conference on Computing, Communication and Learning, vol.1892, pp.15-26, Springer, March 2024, 10.1007/978-3-031-56998-2_2       Inproceedings

R. M. Pattanayak, H. S. Behera, and S. Panigrahi,"A novel high order hesitant fuzzy time series forecasting by using mean aggregated membership value with support vector machine", Information Sciences, vol.626, pp.494-523, Elsevier 2023, 10.1016/j.ins.2023.01.075       Article

G. Shial, S. Sahoo, and S. Panigrahi,"An enhanced GWO algorithm with improved explorative search capability for global optimization and data clustering", Applied Artificial Intelligence, vol.37, no.1, pp.e2166232, Taylor & Francis 2023, 10.1080/08839514.2023.2166232       Article

K. Das, S. Das, and S. Panigrahi,"Energy-efficient forecasting of temperature data in sensor cloud system using a hybrid SVM-ANN method", Wireless Personal Communications, vol.129, pp.2929–2944, Springer 2023, 10.1007/s11277-023-10265-y       Article

R. Pradhan, S. Panigrahi, and P. K. Sahu,"Conformational search for the building block of proteins based on the gradient gravitational search algorithm (ConfGGS) using force fields: CHARMM, AMBER, And OPLS-AA", Journal of Chemical Information and Modeling, vol.63, no.2, pp.670–690, American Chemical Society 2023, 10.1021/acs.jcim.2c01398       Article

G. Shial, C. Tripathy, S. Panigrahi, and S. Sahoo,"An Improved GWO algorithm for data clustering", in Computing, Communication and Learning. CoCoLe 2022, vol.1729, pp.79–90, Springer 2023, 10.1007/978-3-031-21750-0_7       Inproceedings

S. S. Pradhan and S. Panigrahi,"Delhi air quality index forecasting using statistical and machine learning models", in AIP Conference Proceedings, vol.2705, no.1, pp.020002, American Institute of Physics, June 2023, 10.1063/5.0133357       Inproceedings

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