کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
5487490 | 1523590 | 2017 | 35 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Performance of the Angstrom-Prescott Model (A-P) and SVM and ANN techniques to estimate daily global solar irradiation in Botucatu/SP/Brazil
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
علوم زمین و سیارات
فیزیک زمین (ژئو فیزیک)
پیش نمایش صفحه اول مقاله
چکیده انگلیسی
This study describes the comparative study of different methods for estimating daily global solar irradiation (H): Angstrom-Prescott (A-P) model and two Machine Learning techniques (ML) - Support Vector Machine (SVM) and Artificial Neural Network (ANN). The H database was measured from 1996 to 2011 in Botucatu/SP/Brazil. Different combinations of input variables were adopted. MBE, RMSE, d Willmott, r and r2 statistical indicators obtained in the validation of A-P and SVM and ANN models showed that: SVM technique has better performance in estimating H than A-P and ANN models. A-P model has better performance in estimating H than ANN.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Atmospheric and Solar-Terrestrial Physics - Volume 160, July 2017, Pages 11-23
Journal: Journal of Atmospheric and Solar-Terrestrial Physics - Volume 160, July 2017, Pages 11-23
نویسندگان
MaurÃcio Bruno Prado da Silva, João Francisco Escobedo, Taiza Juliana Rossi, CÃcero Manoel dos Santos, SÃlvia Helena Modenese Gorla da Silva,