Methodology for estimating solar potential on multiple building rooftops for photovoltaic systems

[1]  J. Kaňuk,et al.  Assessment of photovoltaic potential in urban areas using open-source solar radiation tools , 2009 .

[2]  J. Mubiru,et al.  Estimation of monthly average daily global solar irradiation using artificial neural networks , 2008 .

[3]  Hamdy K. Elminir,et al.  Prediction of hourly and daily diffuse fraction using neural network, as compared to linear regression models , 2007 .

[4]  Adel Mellit,et al.  A simplified model for generating sequences of global solar radiation data for isolated sites: Using artificial neural network and a library of Markov transition matrices approach , 2005 .

[5]  F. S. Tymvios,et al.  Comparative study of Ångström's and artificial neural networks' methodologies in estimating global solar radiation , 2005 .

[6]  Thomas Huld,et al.  PV-GIS: a web-based solar radiation database for the calculation of PV potential in Europe , 2005 .

[7]  Adnan Sözen,et al.  Forecasting based on neural network approach of solar potential in Turkey , 2005 .

[8]  Gabriel López,et al.  Selection of input parameters to model direct solar irradiance by using artificial neural networks , 2004 .

[9]  Jaroslav Hofierka,et al.  A New GIS‐based Solar Radiation Model and Its Application to Photovoltaic Assessments , 2004, Trans. GIS.

[10]  H. Beyer,et al.  Solar energy assessment using remote sensing technologies , 2003 .

[11]  Stuart J. Gadsden,et al.  Putting solar energy on the urban map: a new GIS-based approach for dwellings , 2003 .

[12]  Markus Neteler,et al.  Open Source GIS: A GRASS GIS Approach , 2007 .

[13]  Zekai Şen,et al.  Spatial interpolation and estimation of solar irradiation by cumulative semivariograms , 2001 .