García Ruiz, Ignacio
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García Ruiz
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Ignacio
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Ingeniería
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ISC. Institute of Smart Cities
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Publication Open Access Two new models of direct luminous efficacy under clear sky conditions for daylighting in Burgos, Spain(Elsevier, 2024-09-01) Dieste-Velasco, María Isabel; García Ruiz, Ignacio; González Peña, David; Alonso-Tristán, Cristina; Ingeniería; Ingeniaritza; Institute of Smart Cities - ISCThe use of daylight in buildings contributes to energy savings while significantly improving visual comfort and well-being. It is therefore very important to be able to quantify illuminance to take advantage of daylight. Although several models have been proposed in recent years to determine global and diffuse illuminance, the same may not be said of direct solar illuminance, which situates this study in an area of noteworthy scientific and technological interest. Two luminous efficacy models for clear sky conditions are proposed and the results of benchmarking with previous models from the literature are presented. Data collected in Burgos (Spain) were analyzed. Specifically, eight previous models for the prediction of direct illuminance were compared with our two new models. The two new models predicted illuminance more accurately than most of the classic models. Specifically, running the models on the training data yielded Root Mean Square Error (RMSE) values of 2.58 % and 2.76 % for the first and the second model, respectively. Likewise, the test data yielded RMSE values of 3.31 % and 3.49 %, and the Mean Bias Error values with the training data were 0.06 % and 0.11 %, respectively. The models achieved high accuracy levels with both the training and the test data sets.Publication Open Access Ultraviolet erythemal irradiance (UVER) under different sky conditions in Burgos, Spain: multilinear regression and artificial neural network models(MDPI, 2023) García-Rodríguez, Sol; García-Rodríguez, Ana; Granados-López, D.; García Ruiz, Ignacio; Alonso-Tristán, Cristina; Ingeniería; Ingeniaritza; Institute of Smart Cities - ISCDifferent strategies for modeling Global Horizontal UltraViolet Erythemal irradiance (GHUVE) based on meteorological parameters measured in Burgos (Spain) have been developed. The experimental campaign ran from September 2020 to June 2022. The selection of relevant variables for modeling was based on Pearson’s correlation coefficient. Multilinear Regression Model (MLR) and artificial neural network (ANN) techniques were employed to model GHUVE under different sky conditions (all skies, overcast, intermediate, and clear skies), classified according to the CIE standard on a 10 min basis. ANN models of GHUVE outperform those based on MLR according to the traditional statistical indices used in this study (R2, MBE, and nRMSE). Moreover, the work proposes a simple all-sky ANN model of GHUVE based on usually recorded variables at ground meteorological stations.