Dr. Amit Kumar Yadav

Assistant Professor
National Institute of Technology Sikkim, India


Highest Degree
Ph.D. in Solar Power Generation from National Institute of Technology, India

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Area of Interest:

Physical Science Engineering
Artificial Neural Network
Renewable Energy
Sustainability
Solar Cell

Selected Publications

  1. Yadav, A.K., V. Sharma, H. Malik and S.S. Chandel, 2017. Daily array yield prediction of grid-interactive photovoltaic plant using relief attribute evaluator based radial basis function neural network. Renew. Sustain. Energy Rev., 10.1016/j.rser.2017.06.023.
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  2. Yadav, A.K. and S.S. Chandel, 2017. Identification of relevant input variables for prediction of 1-minute time-step photovoltaic module power using artificial neural network and multiple linear regression models. Renew. Sustain. Energy Rev., 77: 955-969.
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  3. Khan, M.J., A.K. Yadav, L. Mathew and S. Chatterji, 2017. Techno economic feasibility analysis of different combinations of PV-wind-diesel-battery hybrid system for telecommunication applications in different cities of Punjab, India. Renew. Sustain. Energy Rev., 76: 577-607.
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  4. Yadav, A.K., H. Malik and S.S. Chandel, 2015. Application of rapid miner in ANN based prediction of solar radiation for assessment of solar energy resource potential of 76 sites in Northwestern India. Renew. Sustain. Energy Rev., 52: 1093-1106.
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  5. Yadav, A.K. and S.S. Chandel, 2015. Solar energy potential assessment of western Himalayan Indian state of Himachal Pradesh using J48 algorithm of WEKA in ANN based prediction model. Renew. Energy, 75: 675-693.
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  6. Ramasamy, P., S.S. Chandel and A.K. Yadav, 2015. Wind speed prediction in the mountainous region of India using an artificial neural network model. Renew. Energy, 80: 338-347.
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  7. Yadav, A.K., H. Malik and S.S. Chandel, 2014. Selection of most relevant input parameters using WEKA for artificial neural network based solar radiation prediction models. Renew. Sustain. Energy Rev., 31: 509-519.
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  8. Yadav, A.K. and S.S. Chandel, 2014. Solar radiation prediction using artificial neural network techniques: A review. Renew. Sustain. Energy Rev., 33: 772-781.
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  9. Yadav, A.K. and S.S. Chandel, 2013. Tilt angle optimization to maximize incident solar radiation: A review. Renew. Sustain. Energy Rev., 23: 503-513.
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  10. Malik, H., A.K. Yadav, S. Mishra and T. Mehto, 2013. Application of neuro-fuzzy scheme to investigate the winding insulation paper deterioration in oil-immersed power transformer. Int. J. Electr. Power Energy Syst., 53: 256-271.
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  11. Yadav, A.K. and S.S. Chandel, 2012. Artificial neural network based prediction of solar radiation for Indian stations. Int. J. Comput. Applic., 50: 1-4.

  12. Rahi, O.P., A.K. Yadav, H. Malik, Abdul Azeem and Bupesh Kr, 2012. Power system voltage stability assessment through artificial neural network. Proc. Eng., 30: 53-60.
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  13. Malik, H., Mantosh Kr, Tarkeshwar, A.K. Yadav and B. Anil Kr., 2012. Application of physical-chemical data in estimation of dissolved gases in insulating mineral oil for power transformer incipient fault diagnosis with ANN. Int. J. Comput. Applic., 41: 43-50.

  14. Yadav, A.K., O.P. Rahi, H. Malik and Abdul Azeem, 2011. Design optimization of high frequency power transformer by genetic algorithm and simulated annealing. Int. J. Electr. Comput. Eng., 1: 102-109.

  15. Yadav, A.K., O.P. Rahi, A. Singh and Abdul Azeem, 2011. Estimation of annealing cycle in production process of core using artificial neural network. Int. J. Recent Trends Eng. Technol., 5: 202-204.
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  16. Yadav, A.K., Abdul Azeem and A. Singh, 2011. Economic dispatch using genetic algorithm. Int. J. Electron. Electr. Commun. Eng., 3: 1-4.

  17. Yadav, A.K., A. Singh, Abdul Azeem and O.P. Rahi, 2011. Application of simulated annealing and genetic algorithm in engineering application. Int. J. Adv. Eng. Technol., 1: 81-85.
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  18. Yadav, A.K. and O.P. Rahi, 2011. Optimization of power transformer design using simulated annealing technique. Int. J. Electr. Eng., 4: 191-198.

  19. Abdul Azeem, R.N, Sharma and A.K. Yadav, 2011. Condition assessment of power transformer by swift frequency response analysis. Int. J. Electr. Eng., 4: 199-207.