J
Javier Almorox
Researcher at Technical University of Madrid
Publications - 38
Citations - 1825
Javier Almorox is an academic researcher from Technical University of Madrid. The author has contributed to research in topics: Evapotranspiration & Mean squared error. The author has an hindex of 16, co-authored 33 publications receiving 1493 citations.
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Global solar radiation estimation using sunshine duration in Spain
TL;DR: In this paper, several equations were employed to estimate global solar radiation from sunshine hours for 16 meteorological stations in Spain, using only the relative duration of sunshine, including the original Angstrom-Prescott linear regression and modified functions (quadratic, third degree, logarithmic and exponential functions).
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ANFIS, SVM and ANN soft-computing techniques to estimate daily global solar radiation in a warm sub-humid environment
TL;DR: In this paper, the accuracy and performance of three soft computing techniques (i.e., adaptive neuro-fuzzy inference system (ANFIS), artificial neural network (ANN) and support vector machine (SVM)) were assessed for predicting daily horizontal global solar radiation from measured meteorological variables in the Yucatan Peninsula, Mexico.
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Models for obtaining daily global solar radiation with measured air temperature data in Madrid (Spain)
TL;DR: In this paper, the authors developed a new model for estimating global solar radiation data using temperature measured data for seven stations located in Madrid, Spain, which can be used in the design and estimation of the performance of solar applications.
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Estimation of monthly Angström–Prescott equation coefficients from measured daily data in Toledo, Spain
TL;DR: In this article, the root mean square error (RMSE), the mean bias error (MBE), and the t -statistic were used to estimate the specific monthly global solar radiation.
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Global performance ranking of temperature-based approaches for evapotranspiration estimation considering Köppen climate classes
TL;DR: In this article, the applicability of different TET approaches was evaluated in relation to the Koppen climate classification of the stations, considering a monthly timescale and FAO56 Penman Monteith benchmarks (PM56).