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Faculty oF  EnginEEring & tEchnology


          Research Consultancy (In Numbers):- Nil

          Research Publication (2015-2021) :-( Only SCI/Scopus/UGC Care)

          1.  Khan, S.A., Naim, I., Kusi-Sarpong, S., Gupta, H. and Idrisi, A.R., (2021). A knowledge-based experts’ system for evaluation
             of digital supply chain readiness. Knowledge-Based Systems, p.107262. (SCI Indexed).
          2.  Ishizaka, A., Khan, S.A., Kusi-Sarpong, S. and Naim, I., (2020). Sustainable warehouse evaluation with AHPSort traffic
             light visualisation and post-optimal analysis method. Journal of the Operational Research Society, pp.1-18. (SCI Indexed).
          3.  Ali, R. and Naim, I. (2015) “User Feedback based Metasearching using Neural Network,” International Journal of Machine
             Learning and Cybernetics, ISSN:1868- 8071, Springer-Verlag Berlin Heidelberg. (SCI Indexed).
          4.  Naim, I., Mahara. T. and Khan, S.A. (2020). “Ranking of Univariate Forecasting Techniques for Seasonal Time Series
             using Analytical Hierarchy Process”, Int. J. of Industrial and Systems Engineering., Inderscience. 35(2), pp.196-215
             DOI: 10.1504/IJISE.2020.10020521(SCOPUS Indexed).
          5.  Naim, I., Mahara, T. and Idrisi, A.R., (2018). Effective Short-Term Forecasting for Daily Time Series with Complex Seasonal
             Patterns. Procedia Computer Science, 132,pp.1832-1841.DOI: 10.1016/j.procs.2018.05.136(SCOPUS Indexed).
          6.  Naim, I., Mahara.  T. and Idrisi, A.R. 2018). “Improvement in Procurement through Energy Resource Planning for
             Manufacturing Organization”, Int. J. of Business Excellence, Inderscience. DOI: 10.1504/ IJBEX.2019.10018659 (SCOPUS
             Indexed).
          7.  Naim, I. and Mahara. T. (2018). “Framework to Identify a Set of Univariate Time Series Forecasting Techniques to aid in
             Business Decision Making”,International Journal of Intelligent Enterprise. (SCOPUS Indexed).
          8.  Naim, I., Mahara.  T. and Khan, S.A. (2020). “Day ahead forecast of complex seasonal natural gas data to enhance
             procurement efficiency”, International Journal of Procurement Management, Inderscience. 35(2), pp.196-215
             DOI: 10.1504/IJPM.2020.10028939 (SCOPUS Indexed).



          Declaration: I hereby declare that above mentioned data are correct and in best of my knowledge. In case of any
          discrepancies, I shall be sole responsible.



                                                                                               Name:  Dr. IramNaim








       RESEARCH COMPENDIUM (2015-21)





























          38                Mahatma Jyotiba Phule Rohilkhand University, Bareilly, Uttar Pradesh
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