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• W2000296882 abstract "Solar potential estimation using LiDAR data is an efficient approach for finding suitable roofs for photovoltaic systems' installations. As the amount of LiDAR data increases, the non-parallel methods take considerable time to accurately estimate the solar potential. Although supercomputing provides a possible solution, it is still too expensive and thus infeasible for general usage. Fortunately, the recent graphics processing units (GPUs) can now be utilized to ensure fast computations. This paper proposes a novel method for fast solar potential estimation using GPU-based CUDA technology. This method employs LiDAR data, irradiance measurements, multiresolutional shadowing from solid objects, and heuristic shadowing from vegetation. Experimental results demonstrate the method's effectiveness, in comparison with a multi-core CPU-based approach." @default.
• W2000296882 created "2016-06-24" @default.
• W2000296882 creator A5018002602 @default.
• W2000296882 creator A5061759979 @default.
• W2000296882 date "2013-03-01" @default.
• W2000296882 modified "2023-10-18" @default.
• W2000296882 title "GPU-based roofs' solar potential estimation using LiDAR data" @default.
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• W2000296882 doi "https://doi.org/10.1016/j.cageo.2012.10.010" @default.
• W2000296882 hasPublicationYear "2013" @default.
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