References
- Aly, A. A., El-S. B. Zeidan, and A. M. Hamed. 2011. Performance evaluation of open-cycle solar regenerator using artificial neural network technique. Energy and Buildings 43(2–3):454–7. doi:10.1016/j.enbuild.2010.09.032. http://www.sciencedirect.com/science/article/pii/S0378778810003609
- Bellel, N. 2011. Study of two types of cylindrical absorber of a spherical concentrator. Energy Procedia 6:217–27. doi:10.1016/j.egypro.2011.05.025. http://linkinghub.elsevier.com/retrieve/pii/S1876610211014366
- Benli, H. 2013. Determination of thermal performance calculation of two different types solar air collectors with the use of artificial neural networks. International Journal of Heat and Mass Transfer 60:1–7. doi:10.1016/j.ijheatmasstransfer.2012.12.042. http://linkinghub.elsevier.com/retrieve/pii/S0017931012009982
- Caner, M., E. Gedik, and A. Keçebaş. 2011. Investigation on thermal performance calculation of two type solar air collectors using artificial neural network. Expert Systems with Applications 38(3):1668–74. doi:10.1016/j.eswa.2010.07.090. http://linkinghub.elsevier.com/retrieve/pii/S0957417410007189
- Clausing, A. M. M, J. M. M. Waldvogel, and L. D. D. Lister. 1987. Natural convection from isothermal cubical cavities with a variety of side-facing apertures.” Journal of Heat Transfer (Transactions of the ASME (American Society of Mechanical Engineers), Series C);(United States) 109(2):407–12. http://www.osti.gov/energycitations/product.biblio.jsp?osti_id=6078499
- Climate of Tehran. 2013. Irantour.org. http://www.irantour.org/Iran/Climate.html, Accessed on Apr. 2.
- Curtiss, P. S., M. J. Brandemuehl, and J. F. Kreider. 1994. Energy management in central HVAC plants using neural networks. ASHRAE Transactions 100(1):476–93.
- Duffie, J. A. and W. A. Beckman. 2006. Solar Engineering of Thermal Processes. Wiley. http://www.amazon.com/Solar-Engineering-Thermal-Processes-Duffie/dp/0471698679
- Eswararmoorthy, M. and S. Shanmugam. 2010. Thermodynamic analysis of solar parabolic dish thermoelectric generator. International Journal of Renewable Energy Technology 1(3):348. doi:10.1504/IJRET.2010.032188. http://www.inderscience.com/link.php?id=32188
- Fan, H., R. Singh, and A. Akbarzadeh. 2011. Electric power generation from thermoelectric cells using a solar dish concentrator. Journal of Electronic Materials 40(5):1311–20. doi:10.1007/s11664-011-1625-x. http://link.springer.com/10.1007/s11664-011-1625-x
- Fang, J. B., J. J. Wei, X. W. Dong, and Y. S. Wang. 2011. Thermal performance simulation of a solar cavity receiver under windy conditions. Solar Energy 85(1):126–38. doi:10.1016/j.solener.2010.10.013. http://linkinghub.elsevier.com/retrieve/pii/S0038092X10003191
- Gandhidasan, P. and M.A. Mohandes. 2011a. Artificial neural network analysis of liquid desiccant dehumidification system. Energy 36(2):1180–6. doi:10.1016/j.energy.2010.11.030. http://linkinghub.elsevier.com/retrieve/pii/S0360544210006754
- Gandhidasan, P. and M. a. Mohandes. 2011b. Artificial neural network analysis of liquid desiccant dehumidification system. Energy 36(2):1180–6. doi:10.1016/j.energy.2010.11.030. http://linkinghub.elsevier.com/retrieve/pii/S0360544210006754
- Haykin, S. S. 1994. Neural Networks: A Comprehensive Foundation. Macmillan. http://books.google.com/books?id=PSAPAQAAMAAJ
- Hess, J. L. 1973. Analytic solutions for potential flow over a class of semi-infinite two-dimensional bodies having circular-arc noses. Journal of Fluid Mechanics 60(02):225–39. doi:http://dx.doi.org/10.1017/S0022112073000133. http://journals.cambridge.org/abstract_S0022112073000133
- Jiang, Y. 2008. Prediction of monthly mean daily diffuse solar radiation using artificial neural networks and comparison with other empirical models. Energy Policy 36(10):3833–7. doi:10.1016/j.enpol.2008.06.030. http://linkinghub.elsevier.com/retrieve/pii/S0301421508003133
- Kah, A. H., Q. Y. San, S. C. Guan, W. C. Kiat, and Y. C. Koh. 1995. “Smart air-conditioning system using multilayer perceptron neural network with a modular approach.” In Proceedings of ICNN’95 - International Conference on Neural Networks, 5:2314–2319.IEEE. doi:10.1109/ICNN.1995.487722. http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=487722
- Kalogirou, S. A. 2001. Artificial neural networks in renewable energy systems applications: A review. Renewable and Sustainable Energy Reviews 5(4):373–401. doi:10.1016/S1364-0321(01)00006-5. http://linkinghub.elsevier.com/retrieve/pii/S1364032101000065
- Kalogirou, S. A. 2006. Prediction of flat-plate collector performance parameters using artificial neural networks. Solar Energy 80(3):248–59. doi:10.1016/j.solener.2005.03.003. http://linkinghub.elsevier.com/retrieve/pii/S0038092X0500099X
- Kalogirou, S. A. and M. Bojic. 2000. Artificial neural networks for the prediction of the energy consumption of a passive solar building. Energy 25(5):479–1. doi:http://dx.doi.org/10.1016/S0360-5442(99)00086-9. http://dx.doi.org/10.1016/S0360-5442(99)00086-9
- Kalogirou, S. A, S. Panteliou, and A. Dentsoras. 1999. Artificial neural networks used for the performance prediction of a thermosiphon solar water heater. Renewable Energy 18(1):87–99. doi:10.1016/S0960-1481(98)00787-3. http://linkinghub.elsevier.com/retrieve/pii/S0960148198007873
- Kalogirou, S. A. S.A., C. C. Neocleous, and C. N Schizas. 1998. Artificial neural networks for modelling the starting-up of a solar steam-generator. Applied Energy 60(2):89–100. doi:http://dx.doi.org/10.1016/S0306-2619(98)00019-1. http://dx.doi.org/10.1016/S0306-2619(98)00019-1
- Kalogirou, S. A., S. Panteliou, and A. Dentsoras. 1999. Modeling of solar domestic water heating systems using artificial neural networks. Solar Energy 65(6):335–42. doi:10.1016/S0038-092X(99)00013-4. http://linkinghub.elsevier.com/retrieve/pii/S0038092X99000134
- Kamthania, D. and G. N. Tiwari. 2012. Performance analysis of a hybrid photovoltaic thermal double pass air collector using ANN. Applied Solar Energy 48(3):186–92. doi:10.3103/S0003701X12030073. http://www.springerlink.com/index/10.3103/S0003701X12030073
- Kaushika, N. D. and K. S. Reddy. 2000. Performance of a low cost solar paraboloidal dish steam generating system. Energy Conversion and Management 41(7):713–26. doi:10.1016/S0196-8904(99)00133-8. http://linkinghub.elsevier.com/retrieve/pii/S0196890499001338
- Kendoush, A. A. 2009. Theoretical analysis of heat and mass transfer to fluids flowing across a flat plate. International Journal of Thermal Sciences 48(1):188–94. doi:10.1016/j.ijthermalsci.2008.03.010. http://linkinghub.elsevier.com/retrieve/pii/S1290072908000719
- Keyhani, A., M. Ghasemi-Varnamkhasti, M. Khanali, and R. Abbaszadeh. 2010. An assessment of wind energy potential as a power generation source in the capital of Iran, Tehran. Energy 35(1):188–201. doi:10.1016/j.energy.2009.09.009. http://linkinghub.elsevier.com/retrieve/pii/S0360544209003958
- Koenig, A. A. A. and M. Marvin. 1981. Convection heat loss sensitivity in open cavity solar receivers. Final Report, DOE Contract No. EG77-C-04-3985, Department of Energy, Oak Ridge, Tennessee. http://scholar.google.com/scholar?hl=en&btnG=Search&q=intitle:Convection+heat+loss+sensitivity+in+open+cavity+solar+receivers#0
- Kothandaraman, C. P. 2006. Fundamentals of Heat and Mass Transfer. New Age International. http://books.google.com/books?id=hIviT25WWIEC&pgis=1
- Kreider, J. F. 1991. Artificial neural networks demonstration for automated generation of energy use predictors for commercial buildings. Ashrae Transactions 97(1):775–9.
- Le Quere, P., J. A. C. Humphrey, and F. S. Sherman. 1981. Numerical calculation of thermally driven two-dimensional unsteady laminar flow in cavities of rectangular cross section. Numerical Heat Transfer 4(3):249–83. doi:10.1080/01495728108961792. http://www.tandfonline.com/doi/abs/10.1080/01495728108961792
- Le Quere, P., F. Penot, and M. Mirenayat. 1981. “Experimental study of heat loss through natural convection from an isothermal cubic open cavity.” In Proceedings DOE/SERI/SNLL Workshop on Convective Losses from Solar Receivers, pp. 165–74.
- Ma, R. Y. 1993. Wind Effects on Convective Heat Loss from a Cavity Receiver for a Parabolic Concentrating Solar Collector. Sandia National Laboratories.
- Mellit, A. and S. A. Kalogirou. 2008. Artificial intelligence techniques for photovoltaic applications: A REVIEW. Progress in Energy and Combustion Science 34(5):574–632. doi:10.1016/j.pecs.2008.01.001. http://linkinghub.elsevier.com/retrieve/pii/S0360128508000026
- Mohanraj, M., S. Jayaraj, and C. Muraleedharan. 2008. Modeling of a direct expansion solar assisted heat pump using artificial neural networks. International Journal of Green Energy 5(6):520–32. doi:10.1080/15435070802498499. http://www.tandfonline.com/doi/abs/10.1080/15435070802498499
- Muñoz, J., A. Abánades, and J. M. Martínez-Val. 2009. A conceptual design of solar boiler. Solar Energy 83(9):1713–22. doi:10.1016/j.solener.2009.06.009. http://linkinghub.elsevier.com/retrieve/pii/S0038092X09001339
- Paitoonsurikarn, S., T. Taumoefolau, and K. Lovegrove. 2004. “Estimation of convection loss from paraboloidal dish cavity receivers.” In Proceedings of 42nd Conference of the Australia and New Zealand Solar Energy Society (ANZSES), Perth, Australia.
- Purohit, I. 2010. Testing of solar cookers and evaluation of instrumentation error. Renewable Energy 35(9):2053–64. doi:10.1016/j.renene.2010.02.006. http://linkinghub.elsevier.com/retrieve/pii/S0960148110000558
- Rafeeu, Y. and M. Z. a. Ab Kadir. 2012. Thermal performance of parabolic concentrators under malaysian environment: A case study. Renewable and Sustainable Energy Reviews 16(6):3826–35. doi:10.1016/j.rser.2012.03.041. http://linkinghub.elsevier.com/retrieve/pii/S1364032112002249
- Reddy, K. S. and G. Veershetty. 2013. Viability analysis of solar parabolic dish stand-alone power plant for Indian conditions. Applied Energy 102:908–22. doi:10.1016/j.apenergy.2012.09.034. http://linkinghub.elsevier.com/retrieve/pii/S0306261912006757
- Santos, N. I., A. M. Said, D. E. James, and N. H. Venkatesh. 2012. Modeling solar still production using local weather data and artificial neural networks. Renewable Energy 40(1):71–9. doi:10.1016/j.renene.2011.09.018. http://linkinghub.elsevier.com/retrieve/pii/S0960148111005362
- Sardeshpande, V. R., A. G. Chandak, and I. R. Pillai. 2011. Procedure for thermal performance evaluation of steam generating point-focus solar concentrators. Solar Energy 85(7):1390–8. doi:10.1016/j.solener.2011.03.018. http://linkinghub.elsevier.com/retrieve/pii/S0038092X11001010
- Shuai, Y., X. Xia, and H. Tan. 2010. Numerical simulation and experiment research of radiation performance in a dish solar collector system. Frontiers of Energy and Power Engineering in China 4(4):488–95. doi:10.1007/s11708-010-0007-z. http://link.springer.com/10.1007/s11708-010-0007-z
- Shuai, Y., X.-L. Xia, and H.-P. Tan. 2008. Radiation performance of dish solar concentrator/cavity receiver systems. Solar Energy 82(1):13–21. doi:10.1016/j.solener.2007.06.005. http://linkinghub.elsevier.com/retrieve/pii/S0038092X07001235
- Siebers, D. L. and J. S. Kraabel. 1984. Estimating Convective Energy Losses from Solar Central Receivers. Livermore, CA: Sandia National Labs.
- Sözen, A., E. Arcaklioğlu, and M. Özalp. 2004. Estimation of solar potential in turkey by artificial neural networks using meteorological and geographical data. Energy Conversion and Management 45(18–19):3033–52. doi:10.1016/j.enconman.2003.12.020. http://linkinghub.elsevier.com/retrieve/pii/S0196890404000172
- Stine, W. B. and C. G. McDonald. 1989. “Cavity receiver convective heat loss.” In International Solar Energy Society, Solar World Congress ( 1989, Kobe, Japon).
- Sukhatme. 2008. Solar Energy: Principles of Thermal Collection and Storage. Tata McGraw-Hill Education. http://books.google.com/books?id=O8IMS-jq6skC&pgis=1
- Wang, M. and K. Siddiqui. 2010. The impact of geometrical parameters on the thermal performance of a solar receiver of dish-type concentrated solar energy system. Renewable Energy 35(11):2501–13. doi:10.1016/j.renene.2010.03.021. http://dx.doi.org/10.1016/j.renene.2010.03.021
- Wu, S.-Y., L. Xiao, Y. Cao, and Y.-R. Li. 2010. A parabolic dish/AMTEC solar thermal power system and its performance evaluation. Applied Energy 87(2):452–62. doi:10.1016/j.apenergy.2009.08.041. http://linkinghub.elsevier.com/retrieve/pii/S0306261909003742
- Wu, Y. C. and L. C. Wen. 1978. Solar receiver performance of point focusing collector system. American Society of Mechanical Engineers. http://adsabs.harvard.edu/abs/1978asme.meetR.....W.
- Xiao, L., S.-Y. Wu, and Y.-R. Li. 2012. Numerical study on combined free-forced convection heat loss of solar cavity receiver under wind environments. International Journal of Thermal Sciences 60:182–94. doi:10.1016/j.ijthermalsci.2012.05.008. http://linkinghub.elsevier.com/retrieve/pii/S1290072912001585
- Xie, H., L. Liu, F. Ma, and H. Fan. 2009. “Performance prediction of solar collectors using artificial neural networks.” In 2009 International Conference on Artificial Intelligence and Computational Intelligence, pp. 573–6. IEEE. doi:10.1109/AICI.2009.344. http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=5376446
- Zárate, L. E., E. M. D. Pereira, J. P. D. Silva, R. Vimeiro, and A. S. C. Diniz. 2004. “Neural representation of a solar collector with statistical optimization of the training set.” In Innovations in Applied Artificial Intelligence SE - 10, edited by Bob Orchard, Chunsheng Yang, and Moonis Ali, 3029:87–96. Springer Berlin Heidelberg. doi:10.1007/978-3-540-24677-0_10. http://dx.doi.org/10.1007/978-3-540-24677-0_10