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Journal of Solar Energy
Volume 2015, Article ID 410684, 13 pages
http://dx.doi.org/10.1155/2015/410684
Research Article

Spatial Approach of Artificial Neural Network for Solar Radiation Forecasting: Modeling Issues

1School of Engineering, Indian Institute of Technology Mandi (IIT Mandi), Room No. 106, Mandi Campus, Mandi 175005, India
2Mechanical Engineering Department, Indian Institute of Technology Roorkee (IITR), Roorkee 247667, India
3School of Computing and Electrical Engineering, Indian Institute of Technology Mandi (IIT Mandi), Mandi 175005, India

Received 25 September 2014; Revised 5 December 2014; Accepted 18 December 2014

Academic Editor: Jayasundera M. S. Bandara

Copyright © 2015 Yashwant Kashyap et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Citations to this Article [2 citations]

The following is the list of published articles that have cited the current article.

  • Yashwant Kashyap, Ankit Bansal, and Anil K. Sao, “Solar radiation forecasting with multiple parameters neural networks,” Renewable and Sustainable Energy Reviews, vol. 49, pp. 825–835, 2015. View at Publisher · View at Google Scholar
  • Marcelo D. Cabezas, Jorge A. Hawryluk, Juan I. Franco, and Héctor J. Fasoli, “A Simple and Inexpensive Method for Evaluating the Photovoltaic Potential: Its Validation in Buenos Aires and Antarctica,” Journal of Solar Energy, vol. 2016, pp. 1–8, 2016. View at Publisher · View at Google Scholar