Open Access
MATEC Web of Conferences
Volume 13, 2014
ICPER 2014 - 4th International Conference on Production, Energy and Reliability
Article Number 02015
Number of page(s) 7
Section Energy and Fuel Technology
Published online 17 July 2014
  1. Duffie J.A. & Beckman W.A., “Solar Engineering of Thermal Processes”, John Wiley and Sons, New York, USA. (2006). [Google Scholar]
  2. Mekhilef S., Safari A., Mustaffa W. E. S., Saidur R., Omar R. & Younis, “Solar energy in Malaysia: Current state and prospects.” Renewable and Sustainable Energy Reviews, 16 (1),pp. 386–396, (2012). [Google Scholar]
  3. Muzathik A.M., Nik W.B.W., Ibrahim M.Z., Samo K.B., Sopian K. & Alghoul M.A., “Daily Global Solar Radiation Estimate Based on Sunshine Hours”, International Journal of Mechanical and Materials Engineering, Vol. 6, pp. 75–80,(2011). [Google Scholar]
  4. Sopian K. Othman M.Y., “Estimation of monthly average daily global solar radiation in Malaysia”, Renewable Energy, 2, 319–325, (1992). [CrossRef] [Google Scholar]
  5. Khatib T, Mohamed A, Mahmoud M. & Sopian K., “Modeling of Daily Solar Energy on a Horizontal Surface for Five Main Sites in Malaysia”, International Journal of Green Energy, pp. 795–819, (2011). [CrossRef] [Google Scholar]
  6. Muzathik A.M., “Potential of Global Solar Radiation in Terengganu, Malaysia”. International Journal of Energy Engineering, Vol. 3,pp.103–136, (2013). [Google Scholar]
  7. Muzathik A.M., “Potential of Global Solar Radiation in Terengganu, Malaysia”. International Journal of Energy Engineering, Vol. 3, pp. 130 [Google Scholar]
  8. Khatib T, Mohamed A & Sopian K., “A Review of Solar Energy Modeling Techniques”, Renewable and Sustainable Energy Reviews, (2012). [Google Scholar]
  9. Dhar V.K., Tickoo A.K., Koul R. & Dubey B.P., “Comparative performance of some popular artificial neural network algorithms on benchmark and function approximation problems”, Indian Academy of Sciences, Vol. 74, pp. 307–324, (2009). [Google Scholar]
  10. Adamowski J. & Karapataki C., “Comparison of Multivariate Regression and Artificial Neural Networks for Peak Urban Water-Demand Forecasting: Evaluation of different ANN learning algorithms”, Journal of Hydrologic Engineering, pp. 729–743, (2010). [CrossRef] [Google Scholar]
  11. Sivamadhavi V. & Selvaraj R.S., “Prediction of Monthly Mean Daily Global Solar Radiation using Artificial Neural Network”, Journal Earth System Science, pp. 1501–1510, (2012). [CrossRef] [Google Scholar]
  12. Chayjan R.A. & Esna-Ashari M., “Comparison between Artificial Neural Networks and Mathematical Models for Equilibrium Moisture Characteristics Estimation in Raisin”, Agricultural Engineering International, Vol. 12, (2010). [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.