Publications

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  • INTERNATIONAL JOURNALS
  • INTERNATIONAL CONFERENCES
  • BOOK CHAPTERS
  • EDITED BOOKS
  • EDITORIAL
  • Sibarama Panigrahi, and H. S. Behera*. "A hybrid ETS–ANN model for time series forecasting." Engineering Applications of Artificial Intelligence 66 (2017): 49-59. [IF:3.737]
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  • Sibarama Panigrahi*. "A novel hybrid chemical reaction optimization algorithm with adaptive differential evolution mutation strategies for higher order neural network training." International Arab Journal of Information Technology 14(2017): 18-25. [IF:0.66]
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  • Sibarama Panigrahi, and H. S. Behera*. "Time Series Forecasting Using Differential Evolution-Based ANN Modelling Scheme." Arabian Journal for Science and Engineering 45(2020): 11129-11146. [IF:1.035]
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  • R. M. Pattanayak, Sibarama Panigrahi, and H. S. Behera*. "High-order fuzzy time series forecasting by using membership values along with Data and Support Vector Machine." Arabian Journal for Science and Engineering 45 (2020): 10311-10325. [IF:1.035]
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  • Sibarama Panigrahi, and H. S. Behera*. "A study on leading machine learning techniques for high order fuzzy time series forecasting." Engineering Applications of Artificial Intelligence 87 (2020): 103245. [IF:6.212]
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  • Sibarama Panigrahi*, R. M. Pattanayak, P. K. Sethy, S. K. Behera. "Forecasting of Sunspot Time Series Using a Hybridization of ARIMA, ETS and SVM Methods." Solar Physics 296 (2021): 1-19. [IF:2.96]
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  • S. K. Purohit, Sibarama Panigrahi*, P. K. Sethy, and S. K. Behera. "Time series forecasting of price of agricultural products using hybrid methods." Applied Artificial Intelligence 35 (2021) 1388-1406. [IF:2.777]
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  • R. M. Pattanayak, H. S. Behera*, and Sibarama Panigrahi. "A novel probabilistic intuitionistic fuzzy set based model for high order fuzzy time series forecasting." Engineering Applications of Artificial Intelligence 99 (2021): 104136. [IF:7.802]
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  • P. K. Sethy, C. Pandey*, M. R. Khan, S. K. Behera, K. Vijaykumar, and Sibarama Panigrahi,"A cost-effective computer-vision based breast cancer diagnosis." Journal of Intelligent & Fuzzy Systems 41(2021):5253-5263. [IF:1.737]
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  • M. K. Kar, S. Kumar, A. K. Singh, and Sibarama Panigrahi*, "Reactive power management by using a modified differential evolution algorithm." Optimal Control Applications and Methods 44(2021): 967-986. [IF:1.5]
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  • M. K. Kar, S. Kumar, A. K. Singh, and Sibarama Panigrahi*, "A modified sine cosine algorithm with ensemble search agent up- dating schemes for small signal stability analysis." International Transactions on Electrical Energy Systems 31(2021): e13058. [IF:1.9]
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  • R. M. Pattanayak, H. S. Behera*, and Sibarama Panigrahi. "A non-probabilistic neutrosophic entropy-based method for high- order fuzzy time-series forecasting." Arabian Journal for Science and Engineering 47 (2022): 1399-1421. [IF:2.9]
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  • R. Pradhan, Sibarama Panigrahi, and P. K. Sahu*, "Implementation of gradient gravitational search algorithm towards con- formational search." Computational and Theoretical Chemistry 1208(2022): 113550. [IF:2.8]
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  • R. Yelchuri, J. K. Dash*, P. Singh, A. Mahapatro, and Sibarama Panigrahi, "Exploiting deep and hand-crafted features for tex- ture image retrieval using class membership." Pattern Recognition Letters 160(2022):163-171. [IF:5.1]
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  • 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 339630,(2022):1-31. [IF:1.9]
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  • S. S. Pradhan, Sibarama Panigrahi*, S. K. Purohit, and J. K. Dash, "Study and development of hybrid and ensemble forecasting models for air quality index forecasting", Expert Systems 40(2023): e13449. [IF:3.3]
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  • R. M. Pattanayak*, H. S. Behera, and Sibarama Panigrahi. "A Novel High Order Hesitant Fuzzy Time Series Forecasting by using mean Aggregated Membership value with Support Vector Machine." Information Sciences 626 (2023): 494-523. [IF:8.23]
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  • R. Pradhan, Sibarama Panigrahi, and P. K. Sahu*, "Conformational search for the building block of proteins based on the gra- dient gravitational search algorithm (ConfGGS) using force fields: CHARMM, AMBER, And OPLS-AA." Journal of Chemical Information and Modeling 63(2023): 670–690. [IF:5.3]
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  • G. Shial, S. Sahoo, and Sibarama Panigrahi*,"An enhanced GWO algorithm with improved explorative search capability for global optimization and data clustering." Applied Artificial Intelligence 37(2023): e2166232. [IF:2.8]
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  • T. K. Behera, S. Sathia, Sibarama Panigrahi, and P. K. Naik*, "Revolutionizing cardiovascular disease classification through machine learning and statistical methods." Journal of Biopharmaceutical Statistics (2024):1-23.[IF:1.36]
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  • S. S. Pradhan and Sibarama Panigrahi*,"A study and development of high-order fuzzy time series forecasting methods for air quality index forecasting." Journal of Forecasting 43(2024): 1-24. [IF:3.4]
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  • A. P. Padhy, Sibarama Panigrahi*, V. P. Singh, and P. Pratyasha, "Model order reduction for SISO and MIMO system using im- proved adaptive differential evolution algorithm", Soft Computing, (2024):1-20. [IF:4.01]
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  • S. K. Purohit and Sibarama Panigrahi*,"Novel deterministic and probabilistic forecasting methods for crude oil price employing optimized deep learning, statistical and hybrid models." Information Sciences 658(2024): 120021. [IF:8.1]
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  • Associate Editor of PLOS One Journal


  • Associate Editor of Scientific Reports Journal

  • Sibarama Panigrahi*, B. Rath, and P. S. Kumar,"A hybrid CRO-K-means algorithm for data clustering." in Computational Intelligence in Data Mining, Vol.3, pp.627-639, Springer 2014. [Scopus]
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  • Sibarama Panigrahi*, H.S. Behera, and A. Abraham, "A Fuzzy Filter Based Hybrid ARIMA-ANN Model For Time Series Forecasting." in Proceedings Of The Eighth International Conference On Soft Computing And Pattern Recognition (SoCPaR 2016), pp.592–601, Springer 2017. [Scopus]
    Paper

  • Sibarama Panigrahi* and H. S. Behera,"An Adaptive Fuzzy Filter-Based Hybrid ARIMA-HONN Model For Time Series Forecasting",in Computational Intelligence In Data Mining: Proceedings Of The International Conference On CIDM 2017, vol.711, pp.841–850, Springer 2018.[Scopus]
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  • Sibarama Panigrahi* and H.S. Behera,"Time series forecasting using a hybrid Jaya-FLANN Model." in 2018 International Conference on Recent Innovations in Electrical, Electronics & Communication Engineering (ICRIEECE), pp.3402-3407, IEEE, Bhubaneswar, India 2018. [Scopus]
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  • R. M. Pattanayak, H. S. Behera*, and Sibarama Panigrahi,"A Multi-step-ahead fuzzy time series forecasting by using hybrid chemical reaction optimization with Pi-sigma higher-order neural network." in Computational Intelligence in Pattern Recognition, pp.1029–1041, Springer 2019. [Scopus]
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  • Sibarama Panigrahi* and H. S. Behera,"Fuzzy time series forecasting: a survey", in Computational Intelligence In Data Mining: Proceedings Of The International Conference On ICCIDM 2018, vol.990, pp.641-651, Springer 2019. [Scopus]
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  • R. M. Pattanayak*, H.S. Behera, and Sibarama Panigrahi,"A Novel Hybrid Differential Evolution-PSNN For Fuzzy Time Series Forecasting." in Computational Intelligence in Data Mining, vol.990, pp.675–687, Springer 2019. [Scopus]
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  • G. Shial, S. Sahoo, and Sibarama 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. [Scopus]
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  • G. Shial, S. Sahoo, and Sibarama 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. [Scopus]
    Paper

  • S. S. Pradhan and Sibarama 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. [Scopus]
    Paper

  • S. S. Pradhan and Sibarama 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. [Scopus]
    Paper

  • G. Shial, C. Tripathy, Sibarama 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. [Scopus]
    Paper

  • S. K. Purohit and Sibarama Panigrahi*,"Ranking optimised statistical models for time series forecasting of crude oil price", in Computing, Communication and Intelligence, vol.1, Taylor and Francis, November 2024. [Scopus]
    Paper

  • S. K. Purohit and Sibarama 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. [Scopus]
    Paper

  • Kadiyam, Aswin Tirumala Someswar, Chinmaya Ranjan Padhan, and Sibarama Panigrahi. "A Study on Object Detection us- ing Faster R-CNN, Retina net, RPN_R_50_FPN, RPN_R_50_C4." In 2024 International Conference on Intelligent Computing and Sustainable Innovations in Technology (IC-SIT), pp. 1-6. IEEE, 2024. [Scopus]
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  • C. Jayanth, and Sibarama Panigrahi. "Classification of Pigmented Skin Lesions using Early Fusion of Multi-Deep Features and Support Vector Machine." In 2024 International Conference on Intelligent Computing and Sustainable Innovations in Technology (IC-SIT), pp. 1-6. IEEE, 2024. [Scopus]
    Paper

  • International Conference on Computation Communication and Learning, by Sibarama Panigrahi, Bibhudatta Sahoo, Sanjaya Kumar Panda, Siba Kumar Udgata AISC series, Springer
    NIT Rourkela, Odisha
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