Modeling Solar Energy Potential in a Tehran Province Using Artificial Neural Networks

REFERENCES

• Acra , A. , Jurdi , M. , Mu'allem , H. , Karahagopian , Y. and Raffoul , Z. 1989 . Water disinfection by solar radiation: Assessment and application , Ottawa Ontario Canada : International Development Research Centre .
   Google Scholar
• Azadeh , A. , Maghsoudi , A. and Sohrabkhani , S. 2009 . An integrated artificial neural networks approach for predicting global radiation . Energy Conversion and Management , 50 : 1497 – 505 .
   Web of Science ®Google Scholar
• Ball , R. A. , Purcell , L. C. and Carey , S. K. 2004 . Evaluation of solar radiation prediction models in North America . Agronomy Journal , 96 : 391 – 97 .
   Web of Science ®Google Scholar
• Barma , S. D. , Das , B. , Giri , A. , Majumder , S. and Bose , P. K. 2011 . Back propagation artificial neural network (BPANN) based performance analysis of diesel engine using biodiesel . Journal of Renewable and Sustainable Energy , 3 : 013101
   Web of Science ®Google Scholar
• Behrang , M. A. , Assareh , E. , Ghanbarzadeh , A. and Noghrehabadi , A. R. 2010 . The potential of different artificial neural network (ANN) techniques in daily global solar radiation modeling based meteorological data . Solar Energy , 84 : 1468 – 80 .
   Web of Science ®Google Scholar
• Benghanem , M. , Mellit , A. and Alamri , S. N. 2009 . ANN-based modeling and estimation of daily global solar radiation data: A case study . Energy Conversion and Management , 50 : 1644 – 55 .
   Web of Science ®Google Scholar
• Bocco , M. , Willington , E. and Arias , M. 2010 . Comparison of regression and neural networks models to estimate solar radiation . Chilean Journal of Agricultural Research , 70 : 428 – 35 .
   Web of Science ®Google Scholar
• Chineke , T. C. 2008 . Equations for estimating global solar radiation in data sparse regions . Renewable Energy , 33 : 827 – 31 .
   Web of Science ®Google Scholar
• Cucumo , M. , De Rosa , A. , Ferraro , V. , Kaliakatsos , D. and Marinelli , V. 2007 . Experimental testing of models for estimation of hourly solar radiation on vertical surfaces Arcavacata di Rende . Solar Energy , 81 : 692 – 95 .
   Web of Science ®Google Scholar
• FAO. 2008. Food and Agricultural Organization www.fao.org (http://www.fao.org)
   Google Scholar
• Hargreaves , G. H. and Samani , Z. A. 1982 . Estimation of potential evapotranspiration . Journal of Irrigation and Drainage Division, Proceedings of the American Society of Civil Engineers , 108 : 223 – 30 .
   Web of Science ®Google Scholar
• Heidari , M. D. and Omid , M. 2010 . Energy use patterns and econometric models of major greenhouse vegetable productions in Iran . Energy , 36 : 220 – 25 .
   Web of Science ®Google Scholar
• IRIMO Islamic Republic of Iran Meteorological Office, Data Center Tehran Iran 1993–2008
   Google Scholar
• Jiang , Y. 2009 . Computation of monthly mean daily global solar radiation in China using artificial neural networks and comparison with other empirical models . Energy , 34 : 1276 – 83 .
   Web of Science ®Google Scholar
• Kiranyaz , S. , Ince , T. , Yildirim , A. and Gabbouj , M. 2009 . Evolutionary artificial neural networks by multi-dimensional particle swarm optimization . Neural Networks , 22 : 1448 – 62 .
   PubMed Web of Science ®Google Scholar
• Krishnaiah , T. , Srinivasa Rao , S. , Madhumurthy , K. and Reddy , K. S. 2007 . Neural network approach for modeling global solar radiation . Journal of Applied Sciences Research , 3 : 1105 – 11 .
   Google Scholar
• Li , H. , Ma , W. , Lian , Y. and Wang , X. 2010 . Estimating daily global solar radiation by day of year in China . Applied Energy , 87 : 3011 – 17 .
   Web of Science ®Google Scholar
• Liu , X. , Mei , X. , Li , Y. , Wang , Q. , Raunsø Jensen , J. , Zhang , Y. and Roy Porter , J. 2009 . Evaluation of temperature-based global solar radiation models in China . Agricultural and Forest Meteorology , 149 : 1433 – 46 .
   Web of Science ®Google Scholar
• May , R. J. , Maier , H. R. and Dandy , G. C. 2010 . Data splitting for artificial neural networks using SOM-based stratified sampling . Neural Networks , 23 : 283 – 94 .
   PubMed Web of Science ®Google Scholar
• Mellit , A. , Benghanem , M. and Kalogirou , S. A. 2006 . An adaptive wavelet-network model for forecasting daily total solar-radiation . Applied Energy , 83 : 705 – 22 .
   Web of Science ®Google Scholar
• Moghaddamnia , A. , Remesan , R. , Hassanpour Kashani , M. , Mohammadi , M. , Han , D. and Piri , J. 2009 . Comparison of LLR, MLP, Elman, NNARX and ANFIS models-with a case study in solar radiation estimation . Journal of Atmospheric and Solar-Terrestrial Physics , 71 : 975 – 82 .
   Web of Science ®Google Scholar
• Mohandes , M. , Rehman , M. S. and Halawani , T. O. 1998 . Estimation of global solar radiation using artificial neural networks . Renewable Energy , 14 : 179 – 84 .
   Web of Science ®Google Scholar
• Mohanraj , M. , Jayaraj , S. and Muraleedharan , C. 2008 . Modeling of a direct expansion solar assisted heat pump using artificial neural networks . International Journal of Green Energy , 5 : 520 – 32 .
   Web of Science ®Google Scholar
• NeuroDimension, Inc. Neurosolution for Excel, 2010 http://www.neurosolutions.com/.checkcitation (http://www.neurosolutions.com/.checkcitation)
   Google Scholar
• Omid , M. , Baharlooei , A. and Ahmadi , H. 2009 . Modeling drying kinetics of pistachio nuts with multilayer feed-forward neural network . Drying Technology , 27 : 1069 – 77 .
   Web of Science ®Google Scholar
• Omid , M. , Mahmoudi , A. and Omid , M. H. 2009 . An intelligent system for sorting pistachio nut varieties . Expert Systems with Applications , 36 : 11528 – 35 .
   Web of Science ®Google Scholar
• Rahimikhoob , A. 2010 . Estimating global solar radiation using artificial neural network and air temperature data in a semi-arid environment . Renewable Energy , 35 : 2131 – 35 .
   Web of Science ®Google Scholar
• Robaa , S. M. 2009 . Validation of existing models for estimation global solar radiation over Egypt . Energy Conservation and Management , 50 : 184 – 93 .
   Web of Science ®Google Scholar
• Ruiz-Arias , J. A. , Alsamamra , H. , Tovar-pescador , J. and Pozo-Vazquez , D. 2010 . Proposal of regressive model for the hourly diffuse solar radiation under all sky condition . Energy Conversion and Management , 51 : 881 – 93 .
   Web of Science ®Google Scholar
• Sabziparvar , A. A. and Shetaee , H. 2007 . Estimation of global solar radiation in arid and semi-arid climates of East and West Iran . Energy , 32 : 649 – 55 .
   Web of Science ®Google Scholar
• Schnitzer , H. , Brunner , G. and Gwehenberger , G. Brunner . 2007 . Minimizing greenhouse gas emissions through the application of solar thermal energy in industrial processes . Journal of Cleaner Production , 15 : 1271 – 86 .
   Web of Science ®Google Scholar
• Senkal , O. 2007 . Modeling of solar radiation using remote sensing and artificial neural network in Turkey . Solar Energy , 81 : 692 – 95 .
   Web of Science ®Google Scholar
• Sozen , A. , Arcaklioglu , E. and Ozalp , M. 2004 . Estimation of solar potential in Turkey by artificial neural networks using meteorological and geographical data . Energy Conversion and Management , 45 : 3033 – 52 .
   Web of Science ®Google Scholar
• Surface meteorology and solar energy (SSE), NASA renewable energy resource website, 2011 http://eosweb.larc.nasa.gov/sse/RETScreen (http://eosweb.larc.nasa.gov/sse/RETScreen)
   Google Scholar
• Tymvios , F. S. , Jacovides , C. P. , Michaelides , S. C. and Scouteli , C. 2005 . Comparative study of Angstrom's and artificial neural network's methodologies in estimating global solar radiation . Solar Energy , 78 : 752 – 62 .
   Web of Science ®Google Scholar
• Zhang , G. , Eddy Patuwo , B. and Hu , M. Y. 1998 . Forecasting with artificial neural networks: The state of art . International Journal of Forecasting , 14 : 35 – 62 .
   Web of Science ®Google Scholar