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Dr. Sibarama Panigrahi

Assistant Professor SUIITComputer Science & Engineering
Cell Phone: +917377302566
Photo of Dr. Sibarama Panigrahi

Biographical Info

  • Educational Qualification
    1. B.Tech(CSE) – BPUT
    2. M.Tech(CSE)- VSSUT, Burla
    3. Ph.D (CSE) – VSSUT, Burla
  • Achievements :
    • UGC-NET, Computer Science & Application
    • GATE – 2011, 2012, 2013
  • Experience:
    • Teaching: 4+ yrs
    • Research: 4+ yrs
  • Area of Specialization :
    • Machine Learning
  • Subjects Taught: Algorithm, Theory of Computation, Compiler Design, Programming and Data Structure, Database Management System, Machine Learning, Soft Computing.
  • Guidance
    • B.Tech: 20
    • M.Tech: 08
  • Training/Workshop: 6
  • SCI JOURNAL PUBLICATIONS
    1

     

    Sibarama Panigrahi, and Himansu Sekhar Behera. “A hybrid ETS–ANN model for time series forecasting.” Engineering Applications of Artificial Intelligence 66 (2017): 49-59. ISSN: 0952-1976 [Elsevier, IF:6.20, SCI, Scopus]
    2 Sibarama Panigrahi, and Himansu Sekhar Behera. “A study on leading machine learning techniques for high order fuzzy time series forecasting.” Engineering Applications of Artificial Intelligence 87 (2020): 103245. ISSN: 0952-1976. [Elsevier, IF:6.20, SCI, Scopus]
    3 Sibarama Panigrahi, and H. S. Behera. “Time Series Forecasting Using Differential Evolution-Based ANN Modelling Scheme.” Arabian Journal for Science and Engineering 45.12 (2020): 11129-11146. ISSN: 2191-4281 [Springer, IF:2.33, SCI, Scopus]
    4 Panigrahi, Sibarama. “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 (IAJIT) 14.1 (2017). ISSN: 1683-3198 [IF:0.66, SCI, Scopus]
    5 Sibarama Panigrahi, Radha Mohan Pattanayak, Prabira Kumar Sethy, Santi Kumari  Behera. “Forecasting of Sunspot Time Series Using a Hybridization of ARIMA, ETS and SVM Methods.” Solar Physics 296.1 (2021): 1-19. ISSN: 0038-0938 [Springer, IF:2.67, SCI, Scopus]
    6 Radha Mohan 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 45.12 (2020): 10311-10325. ISSN: 2191-4281 [Springer, IF:2.33, SCI, Scopus]
    7 Radha Mohan 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. ISSN: 0952-1976 [Elsevier, IF:6.20, SCI, Scopus]
    8 Radha Mohan 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. Accepted (In Press). [Springer, IF:2.33, SCI, Scopus]
     

    9

    Santi Kumari Behera, Prabira Kumar Sethy, Santosh Kumar Sahoo, Sibarama Panigrahi, Sharad Chandra Rajpoot. “On-tree fruit monitoring system using IoT and image analysis.” Concurrent Engineering 29, no. 1 (2021): 6-15. ISSN: 1063-293X [IF:1.01, SCI, Scopus]
    10 Prabira Kumar Sethy, Chanki Pandey, Mohammad Rafique Khan, Santi Kumari Behera, K. Vijaykumar, Sibarama Panigrahi. “A cost-effective computer-vision based breast cancer diagnosis.” Journal of Intelligent & Fuzzy Systems Preprint (2021): 1-11. ISSN: 1064-1246 [IF:1.85, SCI, Scopus]
    11 Manoj Kumar Kar, Sanjay Kumar, Arun Kumar Singh, Sibarama Panigrahi, “A modified Sine Cosine algorithm with ensemble search agent updating operators for small signal stability analysis.” International Transaction on Electrical Energy Systems, Accepted (In Press). ISSN:2050-7038 [Wiley, IF:2.86, SCI, Scopus]
    12 Sourav Kumar Purohit, Sibarama Panigrahi, Prabira Kumar Sethy, Santi Kumari Behera, “Time Series Forecasting of Price of Agricultural Products Using Hybrid Methods”, Applied Artificial Intelligence, pp. 1-19, 2021. DOI: https://doi.org/10.1080/08839514.2021.1981659.[Taylor and Fransis, IF:1.58, SCI, Scopus]
    13 Rojalin Pradhan, Sibarama Panigrahi, Prabhat Kumar Sahu, “Implementation of gradient gravitational search algorithm towards conformational search”, Computational and Theoretical Chemistry, no. 1208, pp. 113550, 2022. [Elsevier, IF:1.92, SCI, Scopus]
  • NTERNATIONAL CONFERENCE PUBLICATIONS
    1 S. Panigrahi, B. Rath, P. S. Kumar “A Hybrid CRO-K-Means Algorithm for Data Clustering,” Computational Intelligence in Data Mining-Volume 3. Springer, New Delhi, 2015. pp. 627-639.ISBN: 978-81-322-2202-6
    2 S. Panigrahi, H. S. Behera, A. Abraham “A Fuzzy Filter Based Hybrid ARIMA-ANN Model for Time Series Forecasting,” International Conference on Soft Computing and Pattern Recognition. Springer, Cham, 2016.ISBN:978-3-319-60617-0
    3 S. Panigrahi, H. S. Behera “An Adaptive Fuzzy Filter-Based Hybrid ARIMA-HONN Model for Time Series Forecasting,” Computational Intelligence in Data Mining. Springer, Singapore, 2019. 841-850.ISBN:978-981-10-8054-8
    4 R. M. Pattanayak, H.S. Behera, S. Panigrahi “A novel hybrid differential evolution PSNN for fuzzy time series forecasting,” Computational Intelligence in Data Mining. Springer, Singapore, 2020. 675-687.ISBN:978-981-10-8054-8
    5 R. M. Pattanayak, H.S. Behera, S. Panigrahi “A multi-step-ahead fuzzy time series forecasting by using hybrid chemical reaction optimization with pi-sigma higher-order neural network,” Computational Intelligence in Pattern Recognition. Springer, Singapore, 2020. 1029-1041.ISBN: 978-981-13-9041-8
    6 S. Panigrahi, H. S. Behera “Fuzzy Time Series Forecasting: A Survey,” Computational Intelligence in Data Mining. Springer, Singapore, 2020. 641-651.ISBN:978-981-10-8054-8
    7 S. Panigrahi, 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), 2018, pp. 3402-3407. IEEE.

    Sponsored R & D Projects

    # Project Details
    1 Title: Big Data Platform for Temporal Storage of Clinical Data of Patients of Cardio Vascular Disease (CVD) and Data Mining for Better Diagnosis and Treatment

    Co-Investigator: Dr. Sibarama Panigrahi

    Funding Agency: Indian Council of Medical Research, Government of India.

    Amount: Rs. 21,15,000/-

    2 Title: Design and Development of Large Scale Time Series Forecasting Methods using Deep Learning Techniques

    Principal Investigator: Dr. Sibarama Panigrahi

    Scheme: Odisha University Research and Innovation Incentivization Plan(OURIIP)

    Funding Agency: OSHEC, Government of Odisha.

    Amount: Rs. 4,50,000/-

    3 Title: Studies on Deep Learning Models for Crude Oil Price Forecasting

    Principal Investigator: Dr. Sibarama Panigrahi

    Scheme: Core Research Grant

    Funding Agency: SERB, Government of India.

    Amount: Rs. 22,07,700/-

    4 Title: Studies on Machine Learning, Statistical and Hybrid Models for Streamflow Forecasting of Mahanadi River

    CO-PI: Dr. Sibarama Panigrahi

    Scheme: Research and Development Project

    Funding Agency: Sambalpur University, Government of Odisha.

    Amount: Rs. 50,000/-

    REVIEWER OF INTERNATIONAL JOURNALS

    1 IEEE Access
    2 Engineering Applications of Artificial Intelligence, Elsevier
    3 Evolutionary Intelligence, Springer
    4 International Journal of Data Science and Analytics, Springer
    5 Plos One
    6 MethodsX, Elsevier
    7 Information Fusion, Elsevier
    8 Pattern Recognition, Elsevier

    RESEARCH PROFILE

    Name Link
    1 Google Scholar https://scholar.google.co.in/citations?user=vB_IQPEAAAAJ&hl=en
    2 Research Gate https://www.researchgate.net/profile/Sibarama_Panigrahi
    3 Scopus https://www.scopus.com/authid/detail.uri?authorId=23467607800
    4 Orcid https://orcid.org/0000-0002-1409-3856
    5 Publons https://publons.com/researcher/3246755/sibarama-panigrahi/

     

Categories: Faculty
Updated 6 months ago.