The Experts below are selected from a list of 2202 Experts worldwide ranked by ideXlab platform
Ali Rahimikhoob - One of the best experts on this subject based on the ideXlab platform.
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comparison of m5 model tree and artificial neural network s methodologies in modelling daily reference evapotranspiration from noaa satellite images
Water Resources Management, 2016Co-Authors: Ali RahimikhoobAbstract:The objective of this study was to compare feed-forward artificial neural network (ANN) and M5 model tree for estimating reference evapotranspiration (ET0) only on the basis of the remote sensing based surface temperature (Ts) data. The input variables for these models were the daytime surface temperature at the cold pixel obtained from the AVHRR/NOAA sensor and Extraterrestrial Radiation (Ra). The study has been carried out in five irrigated units that cultivate sugar cane, which located in the Khuzestan plain in the southwest of Iran. A total of 663 images of NOAA–AVHRR level 1b during the period 1999–2009, covering the area of this study were collected from the Satellite Active Archive of NOAA. The FAO-56 Penman–Monteith model was used as a reference model for assessing the performance of the two above approaches. The study demonstrated that modelling of ET0 through the use of M5 model tree gave better estimates than the ANN technique. However, differences with the ANN model are small. Root mean square error and R2 for the comparison between reference and estimated ET0 for the tested data set using the proposed M5 model are 13.7 % and 0.96, respectively. For the ANN model these values are 14.3 % and 0.95, respectively.
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Comparison between M5 Model Tree and Neural Networks for Estimating Reference Evapotranspiration in an Arid Environment
Water Resources Management, 2014Co-Authors: Ali RahimikhoobAbstract:This paper describes a detailed evaluation of the performance and characteristic behaviour of feed-forward artificial neural network (ANN) and M5 model tree for estimating reference evapotranspiration (ET_0) at four meteorological sites in an arid climate. The input variables for these models were the maximum and minimum air temperature, air humidity and Extraterrestrial Radiation. The FAO-56 Penman–Monteith model was used as a reference model for assessing the performance of the two approaches. The results of this study showed that the ANN estimated ET_0 better than the M5 model tree but both models performed well for the study area and yielded results close to the FAO56-PM method. Root mean square error and R^2 for the comparison between reference and estimated ET_0 for the tested data using the proposed ANN model are 5.6 % and 0.98, respectively. For the M5 model tree method these values are 8.9 % and 0.98, respectively. The overall results are of significant practical use because the temperature and Humidity-based model can be used when Radiation and wind speed data are not available.
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comparison between m5 model tree and neural networks for estimating reference evapotranspiration in an arid environment
Water Resources Management, 2014Co-Authors: Ali RahimikhoobAbstract:This paper describes a detailed evaluation of the performance and characteristic behaviour of feed-forward artificial neural network (ANN) and M5 model tree for estimating reference evapotranspiration (ET 0 ) at four meteorological sites in an arid climate. The input variables for these models were the maximum and minimum air temperature, air humidity and Extraterrestrial Radiation. The FAO-56 Penman–Monteith model was used as a reference model for assessing the performance of the two approaches. The results of this study showed that the ANN estimated ET 0 better than the M5 model tree but both models performed well for the study area and yielded results close to the FAO56-PM method. Root mean square error and R 2 for the comparison between reference and estimated ET 0 for the tested data using the proposed ANN model are 5.6 % and 0.98, respectively. For the M5 model tree method these values are 8.9 % and 0.98, respectively. The overall results are of significant practical use because the temperature and Humidity-based model can be used when Radiation and wind speed data are not available. Copyright Springer Science+Business Media Dordrecht 2014
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estimating global solar Radiation using artificial neural network and air temperature data in a semi arid environment
Renewable Energy, 2010Co-Authors: Ali RahimikhoobAbstract:Global solar Radiation (GSR) data are desirable for many areas of research and applications in various engineering fields. However, GSR is not as readily available as air temperature data. Artificial neural networks (ANNs) are effective tools to model nonlinear systems and require fewer inputs. The objective of this study was to test an artificial neural network (ANN) for estimating the global solar Radiation (GSR) as a function of air temperature data in a semi-arid environment. The ANNs (multilayer perceptron type) were trained to estimate GSR as a function of the maximum and minimum air temperature and Extraterrestrial Radiation. The data used in the network training were obtained from a historical series (1994–2001) of daily climatic data collected in weather station of Ahwaz located in Khuzestan plain in the southwest of Iran. The empirical Hargreaves and Samani equation (HS) is also considered for the comparison. The HS equation calibrated by applying the same data used for neural network training. Two historical series (2002–2003) were utilized to test the network and for comparison between the ANN and calibrated HS method. The study demonstrated that modelling of daily GSR through the use of the ANN technique gave better estimates than the HS equation. RMSE and R2 for the comparison between observed and estimated GSR for the tested data using the proposed ANN model are 2.534 MJ m−2 day−1 and 0.889 respectively.
V Gomez - One of the best experts on this subject based on the ideXlab platform.
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estimation of the diffuse solar irRadiation from global solar irRadiation daily and monthly average daily values
Renewable Energy, 1994Co-Authors: J A Martinezlozano, M P Utrillas, V GomezAbstract:Data sets of total and direct solar irRadiation at Valencia (Spain) measured during the years 1990–1991 have been used to analyze diverse methods of estimating the daily values and monthly average daily values of the diffuse fraction of solar Radiation from the ratio of the total to the Extraterrestrial Radiation (clearness index kt). In the case of daily values, all the methods described in the bibliography have led to significant deviations concerning the experimental values, with a MAD (mean absolute deviation) close to 20%. For the monthly average daily values, the methods based on the PDF (probability density function) of daily values of kt provide more accurate results than the deterministic methods based on the correlation of monthly average daily values of kt.
Tian Pau Chang - One of the best experts on this subject based on the ideXlab platform.
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output energy of a photovoltaic module mounted on a single axis tracking system
Applied Energy, 2009Co-Authors: Tian Pau ChangAbstract:In this study, the electric energy from a photovoltaic module was calculated theoretically at different azimuths and tilt angles in Taiwan. The gain of the module mounted on a single-axis tracking panel relative to a traditional fixed panel was analyzed. To simulate different operation environments, both types of Radiation will be considered in addition to observed Radiation, i.e. the Extraterrestrial Radiation and the global Radiation predicted by an empirical model. The results show that the optimal tilt angle obtained from the observed data is flatter than those from other two Radiation types and becomes flatter while the panel deviates from due south. The yearly gains obtained from the Extraterrestrial, predicted and observed Radiations are 51.4%, 28.5% and 18.7%, respectively, if a single-axis tracked panel is installed with the yearly optimal tilt angle; the similar gains are 45.3%, 25.9% and 17.5%, respectively, while the panel is adjusted to its monthly optimal angle each month. The amount of yearly energy in due west (or east) is less than its maximum in due south by about 11%, 10% and 5% for the Extraterrestrial, predicted and observed Radiation respectively. The yearly conversion efficiency of a fixed module is 10.2%, 9.2% and 8.3% for the Extraterrestrial, predicted and observed Radiation, respectively.
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the sun s apparent position and the optimal tilt angle of a solar collector in the northern hemisphere
Solar Energy, 2009Co-Authors: Tian Pau ChangAbstract:In this paper, the Julian dating system is adopted to calculate the Sun’s apparent position. Both the sunshine duration and the optimal installation angle of a fixed solar collector are obtained for different time periods and latitudes in the northern hemisphere. To simulate different operating environments, both kinds of Radiation flux are considered, i.e. Extraterrestrial Radiation and the global Radiation calculated using an empirical model. The results show that Julian dating system is precise enough to predict the Sun’s locus according to analyses of the solar declination and the azimuth and elevation angles. The orientation that a solar collector must be installed at can be roughly estimated by determining the sunshine duration. The majority of the Sun’s path lies in the southern sky over a year, and hence the sunshine duration in the southern sky is longer, except for locations with latitudes below 1.5°. The yearly optimal angles are positive (approximately 0.91 and 0.76 multiplied by the latitude for Extraterrestrial and global Radiation, respectively), for latitudes below 65o. Above this, the curves are flatter, and the differences between the two types of Radiation flux become greater. The ratio of the yearly irRadiation captured by a collector installed at its yearly optimal angle to that captured by the ground surface increases with latitude, and reaches a maximum of 1.71 and 1.35 near latitudes of 65° for Extraterrestrial and global Radiation, respectively. The efficiency of a solar collector decreases when operating in a cloudy environment. The amount of global Radiation incident on the ground surface is about 0.51–0.66 times that of Extraterrestrial Radiation throughout the hemisphere.
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The gain of single-axis tracked panel according to Extraterrestrial Radiation
Applied Energy, 2009Co-Authors: Tian Pau ChangAbstract:In the present study, the gain in Extraterrestrial Radiation received by a single-axis tracked panel relative to a fixed panel was systematically analyzed over a specific period of time. The dynamic angle that the tracked panel should rotate by in order to follow the sun was derived through a series of spherical trigonometric procedures. The instantaneous incident angle of sunlight upon the panel was then calculated, assuming that the panel would simultaneously follow the sun's position. Thus, instantaneous increments of solar energy received by the tracked panel relative to the fixed panel are originally presented. The results show that the angle the tracked panel has to rotate by is 0° at solar noon, and increases towards dawn or dusk. The incident angle of sunlight upon the tracked panel is always smaller than that upon the fixed panel, except at solar noon. As for panels installed with a yearly optimal tilt angle in Taipei, the gains are between 36.3% and 62.1% for four particular days of year, between 37.8% and 60.8% for the four seasons and 49.3% over the entire year. The amount of Radiation collected by the tracked panel is enhanced as the maximum rotation angle is increased. The irRadiation ratio of the tracked panel to the fixed panel is close to 1.5 for latitudes below 65° and gradually increases for latitudes above this. The yearly optimal tilt angle of a south-facing fixed panel is approximately equal to 0.9 multiplied by the latitude (i.e. 0.9 x [phi]) for latitudes below 65° and is about 56 + 0.4 x ([phi] - 65) otherwise.
Osman Yaldiz - One of the best experts on this subject based on the ideXlab platform.
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Estimation of monthly average daily global Radiation on horizontal surface for Antalya (Turkey)
Renewable Energy, 1999Co-Authors: Can Ertekin, Osman YaldizAbstract:In this study, multiple linear regression models were used to estimate the monthly average daily global Radiation using nine different variables for Antalya, Turkey; the Extraterrestrial Radiation, solar declination, mean relative humidity, ratio of sunshine duration, mean temperature, mean soil temperature, mean cloudiness, mean precipitation and mean evaporation. The results showed that the models can estimate global Radiation within relative error (|e|) of −5.7 and 3.9%, a mean error (MPE) of 2.0% and root-mean square error (RMSE) of 2.5% for Antalya.
J A Martinezlozano - One of the best experts on this subject based on the ideXlab platform.
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estimation of the diffuse solar irRadiation from global solar irRadiation daily and monthly average daily values
Renewable Energy, 1994Co-Authors: J A Martinezlozano, M P Utrillas, V GomezAbstract:Data sets of total and direct solar irRadiation at Valencia (Spain) measured during the years 1990–1991 have been used to analyze diverse methods of estimating the daily values and monthly average daily values of the diffuse fraction of solar Radiation from the ratio of the total to the Extraterrestrial Radiation (clearness index kt). In the case of daily values, all the methods described in the bibliography have led to significant deviations concerning the experimental values, with a MAD (mean absolute deviation) close to 20%. For the monthly average daily values, the methods based on the PDF (probability density function) of daily values of kt provide more accurate results than the deterministic methods based on the correlation of monthly average daily values of kt.
