Статті в журналах: "Radiation Estimation Model"

1

Czekalski, Dariusz, Paweł Obstawski, and Tomasz Bakoń. "Possibilities to Estimate Daily Solar Radiation on 2-Axis Tracking Plane Using a Model Based on Temperature Amplitude." Sustainability 12, no. 23 (November 26, 2020): 9909. http://dx.doi.org/10.3390/su12239909.

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Significant errors may occur when estimating daily solar radiation in central Europe using empirical models based on air temperature (especially in the winter months). The first goal of this article is to investigate to what extent it is possible to increase the accuracy of the Hargreaves and Samani model, by using the calibration dedicated for each month. We also corrected the temperature amplitudes by narrowing the daily intervals from which the minimum and maximum values were taken. The second goal of this article is to compare the precision of the daily solar radiation estimation on the horizontal plane and on the 2-axis tracking plane. The database comprises the series of parallel measurements on both planes over a period of 10 years. We considered two procedures, direct and indirect, for the 2-axis tracking plane. The second procedure, dubbed “the first estimate horizontal than calculate tracking” is based on the strong relationship between daily solar radiations on both planes. The direct procedure allows for a slightly more accurate estimation. The estimation of daily radiation on the 2-axis tracking plane reflects the measured values worse than estimation on the horizontal plane. We discovered that the increase of estimation errors on the 2-axis tracking plane, compared to the horizontal one, is proportional to the increase in the coefficient of variability of the daily solar radiations.

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Kor, Hakan. "Global solar radiation prediction model with random forest algorithm." Thermal Science 25, Spec. issue 1 (2021): 31–39. http://dx.doi.org/10.2298/tsci200608004k.

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Global solar radiation estimation is crucial for regional climate assessment and crop growth. Therefore, studies on the prediction of solar radiation are emerging. With the availability of the public data on solar radiation, computerized models have been developed as well. These predictive models play significant role in determining the potentials of regions suitable for renewable energy generation required by engineering and agricultural activities. Herein a computerized model has been presented for estimating global solar radiation. The model utilizes random forest algorithm and reached predictive value of 93.9%.

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Achour, Lazhar, Malek Bouharkat, Ouarda Assas, and Omar Behar. "Smart model for accurate estimation of solar radiation." Frontiers in Energy 14, no. 2 (November 14, 2017): 383–99. http://dx.doi.org/10.1007/s11708-017-0505-3.

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Suwarno, Suwarno, and Rohana Rohana. "Comparison Model Hargreaves, Annandale and New Model for Estimation of Solar Radiation in Perlis, Malaysia." Indonesian Journal of Electrical Engineering and Computer Science 6, no. 2 (May 1, 2017): 286. http://dx.doi.org/10.11591/ijeecs.v6.i2.pp286-293.

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<p>Sunlight is a potential source of electrical energy in the universe. Utilization of solar radiation is not optimal to be a source of electricity generation. Before harnessed solar radiation in order to know in advance the estimated potential energy. Modelling estimates of solar radiation in three models: models Hargreaves, Annandale and the proposed new model. The new model proposed solar radiation estimates based on models Hargreaves and Annandale. Some models for estimating solar radiation is discussed in this paper which aims to determine the potential of solar radiation into electrical energy potential. A new model is proposed to estimate solar radiation. Comparison of the three models are estimated using statistical analysis e (%), CRM, and RMSE is obtained that the proposed new model is better, when compared to other models.</p>

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5

Tar, Károly, and Andrea Bíróné Kircsi. "A Statistical Model for Estimating the Amount of Monthly Global Radiation in the Horizontal Plane." Meteorology 2, no. 1 (March 10, 2023): 128–45. http://dx.doi.org/10.3390/meteorology2010009.

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In addition to dynamic methods, purely statistical models, i.e., findings from the statistical analysis of the existing measured database, also play an important role in predicting the different characteristics of climate elements. In our article, we try to estimate the monthly amount of global radiation in each day of the month. In our previous articles, we presented the sliding-average model developed for estimating the average or amount of a climatic element, measured over a time interval, from within the interval. A version of this model for estimating the end-of-interval sums, the sliding-sum model, was used to estimate the amount of monthly global radiation. After generating the characteristics required for the estimation and analyzing their properties, we examined the errors of the performed estimation. Our model can also help solar energy users create the schedule.

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Kashcheev, V. V., E. A. Pryakhin, and A. N. Menyajlo. "Methodology for estimating the radiation risk of medical exposure during computed tomography considering the uncertainties of the risk model." "Radiation and Risk" Bulletin of the National Radiation and Epidemiological Registry 32, no. 2 (2023): 47–55. http://dx.doi.org/10.21870/0131-3878-2023-32-2-47-55.

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The paper presents analysis of different factors affecting the uncertainty model for estimating ra-diation risk from computed tomography (CT). Uncertainties in radiation doses estimates caused by measurement (instrumental) errors or used dose estimation methods, the size of the scanned area and the type of CT scanner. The uncertainty of radiation dose due to measurement errors or dose estimation methods, the size of the scanned area and type of a CT scan may cause the uncertainties as well. Data used for calculating equivalent doses in individual organs and tissues and for calculating lifetime radiation risk of cancer development due to routine CT testing were updated. Conversion factors for DLP, a measure of radiation dose a patient received during CT exams of thoracic, abdomen and head organs, were determined and used for conversion of the CT doses to equivalent doses for individual organs and tissues exposed to radiation. Data for 15 state-of-the-art CT scanners with varying scanning geometry were updated. Uncertainties in life-time radiation risk were determined by estimating 95% confidence intervals for mean dose-proportionality ratios. Standard deviations related to specific dose distribution, scanning geometry and other factors that impact on uncertainty of radiation risk estimates were calculated. The standard deviations associated with the specifics of the dose distribution, scanning geometry and other factors affecting the uncertainties of radiation risk assessments were calculated. In the course of simulation modelling, organs and tissues were identified that are most exposed to radiation during CT of the chest, abdomen and head.

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Yusoff, Mohd Irwan, Muhamad Irwanto, Safwati Ibrahim, Gomesh Nair, Syed Idris Syed Hassan, and Muhamad Fitra. "Estimating Daily Solar Radiation Using Hargreaves Model in Eastern Malaysia." Applied Mechanics and Materials 699 (November 2014): 564–69. http://dx.doi.org/10.4028/www.scientific.net/amm.699.564.

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This paper presents the forecasting of solar radiation in Kelantan, Eastern Malaysia for the year of 2011 using Hargreaves model. This estimation is based on latitude and daily minimum and maximum temperature in Kelantan. The measured and estimated solar radiation data were compared for the year 2011 and analyzed using coefficient of residual mass (CRM), root mean squared error (RMSE), coefficient of determination (R2) and percentage error (e). The results showed that the value ofCRMis 0.09, it indicates the tendency of the estimation model to under-estimate the measure solar radiation. Meanwhile, the value ofRMSEis 8.21% and the value ofR2is 0.8661, closed to 1 indicates that about 86.61% of the total variation is explained in the data. For thee, the value is 7.98%, it indicates that the model estimation is good.

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8

Kumar, S., and T. Kaur. "Efficient solar radiation estimation using cohesive artificial neural network technique with optimal synaptic weights." Proceedings of the Institution of Mechanical Engineers, Part A: Journal of Power and Energy 234, no. 6 (October 1, 2019): 862–73. http://dx.doi.org/10.1177/0957650919878318.

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Estimation of solar potential is vital for renewable energy applications. In several studies, artificial neural networks have been employed to model solar radiation using various meteorological parameters. The collection and availability of the most appropriate input parameters is important for getting an accurate artificial neural network model. The present study aims to estimate the global solar radiation using different meteorological parameters and identify the significant parameters based on the analysis of synaptic weights in an artificial neural network model using the connection weight approach. Initially, artificial neural network and empirical models is applied to estimate the solar radiation in Chamba region. The artificial neural network architecture 5-48-15-1 resulted in minimum mean absolute percentage error of 12.15%. The mean absolute percentage error values for linear models are found to be 18.95%, 15.39%, and 21.62%, respectively. Thereafter, connection weight approach is applied to find significant parameters. The efficacy of the approach has been shown through a case study related to estimation of solar radiations in the Hamirpur region situated in the state of Himachal Pradesh (India). Five input parameters, namely temperature (T), relative humidity (RH), clearness index (KT), precipitation (PT), and pressure (P), have been considered to estimate solar radiations using a feed-forward neural network. The proposed approach infers that temperature is the most significant parameter followed by humidity and pressure. The clearness index and precipitation has been found to have the least effect on the estimation of solar radiations. Results also indicate that artificial neural network based technique is more accurate compared to empirical model.

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9

Tian, Lin, Lin Chen, Peng Zhang, Bo Hu, Yang Gao, and Yidan Si. "The Ground-Level Particulate Matter Concentration Estimation Based on the New Generation of FengYun Geostationary Meteorological Satellite." Remote Sensing 15, no. 5 (March 5, 2023): 1459. http://dx.doi.org/10.3390/rs15051459.

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The new-generation FengYun geostationary meteorological satellite has a high spatial and temporal resolution, which is advantageous in environmental assessments and air pollution monitoring. This study researched the ground-level particulate matter concentration estimation, based on satellite-observed radiations. The radiation of ground-level particulate matter is separate from the apparent radiation observed by satellites. The positive correlation between PM2.5 and PM10 is also considered to improve the accuracy of inversion results and the interpretability of the estimation model. Then, PM2.5 and PM10 concentrations were estimated synchronously every 5 min in mainland China based on FY-4A satellite directly observed radiations. The validation results showed that the improved model estimated results were close to the ground site measured results, with a high determination coefficient (R2) (0.89 for PM2.5, and 0.90 for PM10), and a small Root Mean Squared Error (RMSE) (4.69 μg/m3 for PM2.5 concentrations, and 13.77 μg/m3 for PM10 concentrations). The estimation model presented a good performance in PM2.5 and PM10 concentrations during typical haze and dust storm cases, indicating that it is applicable in different weather conditions and regions.

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10

Chaibi, Mohamed, EL Mahjoub Benghoulam, Lhoussaine Tarik, Mohamed Berrada, and Abdellah El Hmaidi. "An Interpretable Machine Learning Model for Daily Global Solar Radiation Prediction." Energies 14, no. 21 (November 5, 2021): 7367. http://dx.doi.org/10.3390/en14217367.

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Machine learning (ML) models are commonly used in solar modeling due to their high predictive accuracy. However, the predictions of these models are difficult to explain and trust. This paper aims to demonstrate the utility of two interpretation techniques to explain and improve the predictions of ML models. We compared first the predictive performance of Light Gradient Boosting (LightGBM) with three benchmark models, including multilayer perceptron (MLP), multiple linear regression (MLR), and support-vector regression (SVR), for estimating the global solar radiation (H) in the city of Fez, Morocco. Then, the predictions of the most accurate model were explained by two model-agnostic explanation techniques: permutation feature importance (PFI) and Shapley additive explanations (SHAP). The results indicated that LightGBM (R2 = 0.9377, RMSE = 0.4827 kWh/m2, MAE = 0.3614 kWh/m2) provides similar predictive accuracy as SVR, and outperformed MLP and MLR in the testing stage. Both PFI and SHAP methods showed that extraterrestrial solar radiation (H0) and sunshine duration fraction (SF) are the two most important parameters that affect H estimation. Moreover, the SHAP method established how each feature influences the LightGBM estimations. The predictive accuracy of the LightGBM model was further improved slightly after re-examination of features, where the model combining H0, SF, and RH was better than the model with all features.

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11

Sa’id, R. S., S. I. Akor, and U. M. Gana. "Empirical models for estimation of global solar radiation using the monthly average daily sunshine hours data for Makurdi, Benue State." Bayero Journal of Pure and Applied Sciences 12, no. 1 (April 22, 2020): 32–39. http://dx.doi.org/10.4314/bajopas.v12i1.6.

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This paper proposes empirical correlation models for estimating global solar radiation using data of sunshine hours for the location of Makurdi in Benue State of Nigeria. The paper suggests extrapolation of the empirical models for other locations with similar climatic conditions. The proposed models are: Linear, Quadratic, Cubic, Exponential, Power and Logarithmic models. Each of the models is based on Angstrom-Prescott equations for estimating global solar radiation. Any of the models can ease the use of sophisticated equipments, which are expensive, delicate and sometimes develop faults during measurement. The results of the models show that the cubic model is the best with slightly higher coefficient of determination. The coefficient of determination of each of the models was found to be 0.952, 0.965, 0.967, 0.965, 0.948& 0.924 respectively, while the absolute correlation was found to be unity. Errors evaluated include MBE, RMSE and MPE with minimal values. The percentage diffuse and direct solar radiations, clearness index and the diffuse fraction were also estimated using the models. The results of the estimations done using the proposed models indicate that there is an estimated average annual global solar radiation of 6056MJm-2, monthly value of 505MJm-2 and daily insolation of 16.82MJm-2 sufficient enough for maximum solar radiation exploitation. Keywords: Solar Radiation, Empirical Models, Diffuse Radiation, Direct Radiation

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12

Kothan. "An Estimation of X-Radiation Output using Mathematic Model." American Journal of Applied Sciences 8, no. 9 (September 1, 2011): 923–26. http://dx.doi.org/10.3844/ajassp.2011.923.926.

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13

Furukawa, Kyoji, Munechika Misumi, John B. Cologne, and Harry M. Cullings. "A Bayesian Semiparametric Model for Radiation Dose-Response Estimation." Risk Analysis 36, no. 6 (November 19, 2015): 1211–23. http://dx.doi.org/10.1111/risa.12513.

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14

Heinemann, Alexandre Bryan, Pepijn A. J. van Oort, Diogo Simões Fernandes, and Aline de Holanda Nunes Maia. "Sensitivity of APSIM/ORYZA model due to estimation errors in solar radiation." Bragantia 71, no. 4 (2012): 572–82. http://dx.doi.org/10.1590/s0006-87052012000400016.

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Crop models are ideally suited to quantify existing climatic risks. However, they require historic climate data as input. While daily temperature and rainfall data are often available, the lack of observed solar radiation (Rs) data severely limits site-specific crop modelling. The objective of this study was to estimate Rs based on air temperature solar radiation models and to quantify the propagation of errors in simulated radiation on several APSIM/ORYZA crop model seasonal outputs, yield, biomass, leaf area (LAI) and total accumulated solar radiation (SRA) during the crop cycle. The accuracy of the 5 models for estimated daily solar radiation was similar, and it was not substantially different among sites. For water limited environments (no irrigation), crop model outputs yield, biomass and LAI was not sensitive for the uncertainties in radiation models studied here.

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Qian, Budong, Qi Jing, Xuebin Zhang, Jiali Shang, Jiangui Liu, Hui Wan, Taifeng Dong, and Reinder De Jong. "Adapting estimation methods of daily solar radiation for crop modelling applications in Canada." Canadian Journal of Soil Science 99, no. 4 (December 1, 2019): 533–47. http://dx.doi.org/10.1139/cjss-2019-0018.

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Estimating daily solar radiation from common meteorological variables plays an important role in agricultural applications, such as driving crop growth models. Relatively simple and accurate estimation methods, which use only daily air temperature together with precipitation, are often required. Based on all available solar radiation data across Canada, the most common and representative solar radiation models were evaluated. All estimation models provided more accurate estimates, in terms of all performance statistics used in this study, than those extracted directly from a high-resolution global dataset of meteorological forcings for land surface modelling. The DS model adapted from one originally developed for the Canadian Prairies performed better than other representative models for all stations. The DS model was then adapted for regional use in southern Canada, mostly the major agricultural regions. We compared simulated crop yields using the CSM–CERES–wheat and CSM–CROPGRO–canola models driven by observed and estimated daily solar radiation data, and we found a difference of approximately 5% for spring wheat (Triticum aestivum L.) and 12% for canola (Brassica napus L.). Based on the results for two locations under different climate regimes with relatively long records (45 and 40 yr, respectively) of solar radiation data, the models using daily temperature range and precipitation were found to be robust for daily solar radiation estimation for the entire time periods of the data records.

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Gocic, Milan, Mladen Milanovic, and Slavisa Trajkovic. "Effect of solar radiation models on evapotranspiration estimation." Facta universitatis - series: Architecture and Civil Engineering 14, no. 2 (2016): 247–55. http://dx.doi.org/10.2298/fuace1602247g.

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The crop evapotranspiration has the great effect on defining and planning of water resources. The estimation of evapotranspiration depends on various climatic parameters. In this study, the analysis of the effect of solar radiation (Rs) on daily reference evapotranspiration (ET0) was conducted. The FAO-56 Penman-Monteith method (FAO-56 PM) was used for the estimation of ET0 in Serbia at eight meteorological stations for the period 1980-2010. The Rs was estimated using the ten one-parameter global solar radiation models. The ET0 with Almorox and Hontoria model 1 had the smallest deviation related to the ET0 with Angstr?m-Prescott (AP) model, and ET0 with To?rul et al. model 2 and Rietveld model had the greatest deviation from ET0 with AP model.

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Z. Ali, Hussain, Ali M. AL-Salihi, and Ahmed K. AL-Abodee. "Mapping Monthly Average Global Solar Radiation over Iraq Using GIS and Heliosat Model." INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY 15, no. 5 (March 23, 2016): 6724–31. http://dx.doi.org/10.24297/ijct.v15i5.1635.

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The mapping of global solar radiation is important in designing of solar energy system and renewable energy applications, also the global solar radiation estimation and mapping will facilitate engineers and architect purposes and applications. In present paper measured and estimated global solar radiation data was employed. The estimation of global radiation data can give results with acceptable accuracy to establish solar maps of monthly radiation using Geographic Information Systems (GIS) software. Simple Kriging interpolation was used to derive radiation maps over Iraq. Â Different models were employed, namely Spherical, Circular, and Gaussian. Solar radiation data for the years 1985,1990,1995,2000 and 2005 were used for the production of solar radiation maps over Iraq. On average, Iraq receives (5000) kWh/m2 of global solar radiation in year 2005. The highest global solar radiation is estimated at 6790kWh/m2 in September while the lowest is 1660 kWh/m2in December. Cross validation was used to find the best model by comparing the error criteria, namely MPE, RMS, MSPE, RMSS, and ASE. It was found the Spherical model gives best results according to the cross validation error criteria.Mapping Monthly Average Global Solar Radiation over Iraq Using GIS and Heliosat Model

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Barco Jiménez, John, Francisco Eraso Checa, Andrés Pantoja, and Eduardo Caicedo Bravo. "Estimation of Global Solar Radiation Using NNARX Neural Networks Based on the UV Index." Tecnura 25, no. 70 (October 1, 2021): 90–107. http://dx.doi.org/10.14483/22487638.18638.

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Context: This work presents different models based on artificial neural networks, among them NNARX, for estimating global solar radiation from UV index measurements. The objective is to determine the efficiency of the models studied to estimate global solar radiation in terms of the coefficient of determination (R2), the root-mean-square error (RMSE), and the mean absolute error (MAE). Methodology: It is divided into four stages: i) conformation of the training dataset (in this case, it uses a training set of 213.019 data collected over five years in the city of Pasto, Colombia, with the Davis Vantage Pro 2.0 station); ii) pre-processing of data to remove erroneous and unusual data; iii) definition of models based on recurrent and conventional artificial neural networks according to an analysis of topologies, e.g. NNFIR and NNARX; iv) training of the models and evaluation of the estimation efficiency through metrics such as R2, RMSE, and MAE. To validate the model, a new dataset collected during the last year was used, which was not included in the data training. Results: The global solar radiation estimation models based on NNARX show the best estimation efficiency compared to conventional neural networks. The NNARX221 model has an RMSE of 54,32 and a MAE of 18,06 w/m2. Conclusions: NNARX models are highly efficient at estimating global solar radiation, with a coefficient of determination of 0,9697 in the best of cases. The most efficient models are characterized by using two past times and the current UV index instant, and they feed from two past times of their own estimated radiation output. Furthermore, the numerical results show that the contribution of temperature and relative humidity is not relevant to improving the efficiency of the estimation of global solar radiation. These models can be particularly important since they only use measurements made with UV index sensors, which are less expensive than solar radiation ones.

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Mahmoud Sabo, Lurwan, Norman Mariun, Hashim Hizam, Mohd Amran Mohd Radzi, and Azmi Zakaria. "Estimation of solar radiation from digital elevation model in area of rough topography." World Journal of Engineering 13, no. 5 (October 3, 2016): 453–60. http://dx.doi.org/10.1108/wje-08-2016-0063.

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Purpose The purpose of this study is to evaluate the reliability of the technique for estimating solar radiation in areas of rough topography and to detect the source of error and means for improvement. Design/methodology/approach Spatial data of the study area in the form of digital elevation model (DEM) coupled with geographic information system (GIS) were used to estimate the monthly solar radiation at locations with rough topography. The generated data were compared with measured data collected from all the selected locations using NASA data. Findings The results show that the variation in topographic parameters has a strong influence on the amount of solar radiation received by two close locations. However, the method performed well for solar radiation estimated in the areas of rough topography. Research limitations/implications The proposed approach overestimates the monthly solar radiation as compared with NASA data due to the impact of topographic parameters accounted for by the model which are not accounted by conventional methods of measurements. This approach can be improved by incorporating the reflected component of radiation in the model used to estimate the solar radiation implemented in the GIS. Originality/value The approach of using GIS with DEM to estimate solar radiation enables to identify the spatial variability in solar radiation between two closest locations due to the influence of topographic parameters, and this will assist in proper energy planning and decision making for optimal areas of solar photovoltaic installation.

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Duguay, Claude R. "Modelling the radiation budget of alpine snowfields with remotely sensed data: model formulation and validation." Annals of Glaciology 17 (1993): 288–94. http://dx.doi.org/10.3189/s0260305500012982.

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A model for estimating the radiation balance of alpine snowfields is presented. Shortwave and longwave downward flux densities are computed for sloping surfaces using a modified version of the two-stream radiative transfer scheme of Zdunkowski and others (1982). Surface albedo and thermal exitance values are estimated using Landsat-5 Thematic Mapper (TM) imagery and digital terrain data. The LOWTRAN7 radiative transfer code is utilized in order to remove atmospheric effects in satellite imagery as well as calculating solar irradiance within TM spectral bands, for the determination of the near-nadir reflectance of snow. Under a Lambertian assumption, near-nadir reflectance measurements obtained from a few TM bands are used to calculate the total hemispherical reflectance (albedo) of snow. The net all-wave radiation of snowfields is then simulated for the complete day on the same date as that of the Landsat overflight. The model is tested using Landsat TM data acquired in late June 1984, and results compared with field measurements acquired on Niwot Ridge, Colorado, U.S.A. Preliminary results are very encouraging but problems remain in the estimation of surface albedo from near-nadir satellite reflectance measurements of TM. These problems are discussed and recommendations for future model improvements are given.

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Duguay, Claude R. "Modelling the radiation budget of alpine snowfields with remotely sensed data: model formulation and validation." Annals of Glaciology 17 (1993): 288–94. http://dx.doi.org/10.1017/s0260305500012982.

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Анотація:

A model for estimating the radiation balance of alpine snowfields is presented. Shortwave and longwave downward flux densities are computed for sloping surfaces using a modified version of the two-stream radiative transfer scheme of Zdunkowski and others (1982). Surface albedo and thermal exitance values are estimated using Landsat-5 Thematic Mapper (TM) imagery and digital terrain data. The LOWTRAN7 radiative transfer code is utilized in order to remove atmospheric effects in satellite imagery as well as calculating solar irradiance within TM spectral bands, for the determination of the near-nadir reflectance of snow. Under a Lambertian assumption, near-nadir reflectance measurements obtained from a few TM bands are used to calculate the total hemispherical reflectance (albedo) of snow. The net all-wave radiation of snowfields is then simulated for the complete day on the same date as that of the Landsat overflight. The model is tested using Landsat TM data acquired in late June 1984, and results compared with field measurements acquired on Niwot Ridge, Colorado, U.S.A. Preliminary results are very encouraging but problems remain in the estimation of surface albedo from near-nadir satellite reflectance measurements of TM. These problems are discussed and recommendations for future model improvements are given.

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Okundamiya, M. S., and A. N. Nzeako. "Estimation of Diffuse Solar Radiation for Selected Cities in Nigeria." ISRN Renewable Energy 2011 (October 12, 2011): 1–6. http://dx.doi.org/10.5402/2011/439410.

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This study proposes a multivariable model of monthly mean daily diffuse solar radiation on horizontal surfaces for three cities (Abuja, Benin City and Katsina), in Nigeria. The estimation was based on a correlation between clearance index and diffuse to global solar radiation ratio and was computed using monthly mean daily data set for global solar radiation on horizontal surfaces. The predictive efficiency of the proposed model was compared with the observed values and those believed to be universally applicable. The results suggest that the existing methods could be replaced by the developed model for a diffuse solar radiation data generation scheme.

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Naqvi, Asad A., Muhammad Uzair, Maaz Akhtar, Asad A. Zaidi, and Syed Umair Hasan Kazmi. "Statistical Approach to select the Best Suitable Solar Model for Global Radiation: Case Study of Karachi, Pakistan." TECCIENCIA 17, no. 32 (February 2, 2022): 17–27. http://dx.doi.org/10.18180/tecciencia.2022.32.2.

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Utilization of solar energy for the fulfillment of daily routine tasks has gained a lot of interest in the recent past. The complete utilization can be accomplished only if proper solar data is available for a particular site. The measurement of solar data is expensive and time consuming. Different empirical correlations are available for the estimation of solar radiations on a particular site. In this research, monthly average daily solar radiation on horizontal surface is compared with measured data available as typical metrological year, TMY2, and estimated from the different solar models available for Karachi. The models studied are Ahmad models, Raja Models, Hargreaves Model and Black model. The estimation of different empirical correlations and NASA are compared with the measured values. The comparison was done by using statistical techniques like MAPE, MBE, RMSE and t-stats. The results revealed that Hargreaves model is the best model to estimate global radiation for Karachi with minimum value of t-stats while Raja 3 model is the most inappropriate model with highest value of MAPE, RMSE, MBE and t-stat. Overall, the already established empirical correlations can be used for the estimation of solar energy for Karachi for complete utilization of solar energy with minimum errors.

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Swaminathan, V., R. M. Gairola, C. Balaji, and S. P. Venkateshan. "Estimation of Microwave Radiation Intensity from a Multilayered Cloud Model." Journal of Thermophysics and Heat Transfer 19, no. 3 (July 2005): 343–52. http://dx.doi.org/10.2514/1.7256.

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Zhang, Yunhuang, Jean C. Ragusa, and Jim E. Morel. "Model Error Estimation for the Simplified PN Radiation Transport Equations." Nuclear Science and Engineering 194, no. 10 (September 2, 2020): 903–26. http://dx.doi.org/10.1080/00295639.2020.1771141.

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Vafakhah, Mehdi, Anis Nouri, and Sayyed Kazem Alavipanah. "Snowmelt-runoff estimation using radiation SRM model in Taleghan watershed." Environmental Earth Sciences 73, no. 3 (July 3, 2014): 993–1003. http://dx.doi.org/10.1007/s12665-014-3449-5.

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Kaba, Kazım, Mehmet Sarıgül, Mutlu Avcı, and H. Mustafa Kandırmaz. "Estimation of daily global solar radiation using deep learning model." Energy 162 (November 2018): 126–35. http://dx.doi.org/10.1016/j.energy.2018.07.202.

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Makrantoni, Panagiota, Anastasia Tezari, Argyris N. Stassinakis, Pavlos Paschalis, Maria Gerontidou, Pantelis Karaiskos, Alexandros G. Georgakilas, et al. "Estimation of Cosmic-Ray-Induced Atmospheric Ionization and Radiation at Commercial Aviation Flight Altitudes." Applied Sciences 12, no. 11 (May 24, 2022): 5297. http://dx.doi.org/10.3390/app12115297.

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The main source of the ionization of the Earth’s atmosphere is the cosmic radiation that depends on solar activity as well as geomagnetic activity. Galactic cosmic rays constitute a permanent radiation background and contribute significantly to the radiation exposure inside the atmosphere. In this work, the cosmic-ray-induced ionization of the Earth’s atmosphere, due to both solar and galactic cosmic radiation during the recent solar cycles 23 (1996–2008) and 24 (2008–2019), was studied globally. Estimations of the ionization were based on the CRAC:CRII model by the University of Oulu. The use of this model allowed for extensive calculations from the Earth’s surface (atmospheric depth 1033 g/cm2) to the upper limit of the atmosphere (atmospheric depth 0 g/cm2). Monte Carlo simulations were performed for the estimation quantities of radiobiological interest with the validated software DYASTIMA/DYASTIMA-R. This study was focused on specific altitudes of interest, such as the common flight levels used by commercial aviation.

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Akpootu, D. O., S. R. Alaiyemola, M. K. Abdulsalam, G. Bello, M. Umar, S. Aruna, A. K. Isah, Z. Aminu, Z. Abdullahi, and T. O. Badmus. "Sunshine and Temperature Based Models for Estimating Global Solar Radiation in Maiduguri, Nigeria." Saudi Journal of Engineering and Technology 8, no. 05 (May 16, 2023): 82–90. http://dx.doi.org/10.36348/sjet.2023.v08i05.001.

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Анотація:

Nine existing sunshine based models and three existing temperature based models were evaluated and compared to ascertain the most suitable models for estimating global solar radiation in Maiduguri; the most suitable sunshine based and most suitable temperature based models were also compared. The measured monthly average daily global solar radiation, sunshine hours, maximum and minimum temperature meteorological parameters during the period of thirty one years (1980 – 2010) was utilized and the evaluated models were tested statistically using validation indicators of coefficient of determination, Mean Bias Error, Root Mean Square Error, Mean Percentage Error, t – test, Nash – Sutcliffe Equation and Index of Agreement. The results indicated that the linear exponential sunshine based model and the logarithmic temperature based model were found more accurate for global solar radiation estimation in Maiduguri as compared to other evaluated models. Furthermore, the logarithmic temperature based model was found more accurate for estimating global solar radiation as compared to the linear exponential sunshine based model, and this was testified from the figure showing the comparison between the recommended sunshine based and temperature based models in which the recommended temperature based model depicts the best fitting with the measured global solar radiation data.

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Guher, Abdurrahman Burak, Sakir Tasdemir, and Bulent Yaniktepe. "Effective Estimation of Hourly Global Solar Radiation Using Machine Learning Algorithms." International Journal of Photoenergy 2020 (December 9, 2020): 1–26. http://dx.doi.org/10.1155/2020/8843620.

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The precise estimation of solar radiation is of great importance in solar energy applications with respect to installation and capacity. In estimate modelling on selected target locations, various computer-based and experimental methods and techniques are employed. In the present study, the Multilayer Feed-Forward Neural Network (MFFNN), K -Nearest Neighbors ( K -NN), a Library for Support Vector Machines (LibSVM), and M5 rules algorithms, which are among the Machine Learning (ML) algorithms, were used to estimate the hourly average solar radiation of two geographic locations on the same latitude. The input variables that had the most impact on solar radiation were identified and grouped as a result of 29 different applications that were developed by using 6 different feature selection methods with Waikato Environment for Knowledge Analysis (WEKA) software. Estimation models were developed by using the selected data groups and all input variables for each target location. The results show that the estimations developed with the feature selection method were more successful for target locations, and the radiation potentials were similar. The performance of the estimation models was evaluated by comparing each model with different statistical indicators and with previous studies. According to the RMSE, MAE, R 2 , and SMAPE statistical scales, the results of the most successful estimation models that were developed with MFFNN were 0.0508-0.0536, 0.0341-0.0352, 0.9488-0.9656, and 7.77%-7.79%, respectively.

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31

Salhi, Ouassila, Mohammed Diouri, Mohammed Amine Moussaoui, Ibtissam Marsli, and Rajae Meziane. "Estimation of absorptivity of Earth-atmosphere system over the MENA areas." E3S Web of Conferences 314 (2021): 03006. http://dx.doi.org/10.1051/e3sconf/202131403006.

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The developed Annual Columnar Radiative Absorptivity (ACRA19) model that describes, in annual mean, the terrestrial radiation balance of an atmospheric column, allows the determination of the various regional, absorption and reflection of solar and infrared radiation using 2018’s annual data of eight sites in MENA region ( between 22N-38N) of latitude obtained from AERONET and NASA POWER. The atmospheric thermal absorptivity (ATA) is very significant at high temperatures with an average of 0.85±0.1 for 1020 nm and the atmospheric visible absorptivity (AVA) registers 0.36 ± 0.06 when the total optical depth observes its maximum linked to dust aerosol advection.

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32

Hamza, B and Garba, S. "ESTIMATION OF GLOBAL SOLAR RADIATION USING SUNSHINE HOURS IN SOKOTO NIGERIA." International Journal of Applied Science and Engineering Review 03, no. 06 (2022): 173–85. http://dx.doi.org/10.52267/ijaser.2022.3610.

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Анотація:

Inadequate installations of materials such as solar water heater, solar still, solar dryer, and solar cooker etc. Which required solar radiation and maximally, in the area location of is a major problem and this hinders the abundant utilization of solar energy as it can be harnessed directly without any requirement of external energy such as electricity. It is the lack of the information that limits the number of installations in the study area. Therefore, it is compulsory to study and analyzed the solar radiation of our environment to get better view of monitoring the performance of solar energy conversion system in Sokoto State, so that companies and government should know what period or seasons can therefore utilize the abundant solar energy. A new model was developed for estimation the monthly average daily global solar radiation. In this research a modified angstrom model for estimation of global solar radiation in Sokoto, Nigeria using sunshine duration based on meteorological data were used. However, solar radiation estimates are too local since they rely on weather stations or have a resolution that is too satellites. In this work, a model was developed for estimation of global solar radiation on horizontal surface for Sokoto at latitude of m13 13.00E and longitude of 5.250N. Global solar radiation and maximum temperature data for Sokoto were used to fit the Angstrom model, Regression coefficient a, b, and c. 1.12, 0.65, and 0.32 respectively were obtained from the models base on sunshine duration respectively. In order to evaluate the results, three statistical methods have been used namely: mean bias, root mean square, and percentage errors of values -6.47, 6.47 and 41.20% respectively. It was found from statistical model’s performance indicators that the model provides reasonably high degree of precision in the estimation of average global solar radiation on horizontal surfaces.

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Moiseev, A. A. "Model-based estimation of radio parameters." Radio industry 28, no. 3 (August 29, 2018): 31–45. http://dx.doi.org/10.21778/2413-9599-2018-28-3-31-45.

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It’s proposed to use model-based approach for evaluation of radiation parameters observed by passive location facilities. This method is based on model parameters adjustment and interpretation of correspondent parameters values as experimental parameters evaluations. Evaluation adequacy criterion in this case is maximal probability of overlapping of experimental and model ranges of parameters. Preliminary objects selection can be based on frequency or/end directional characteristics of received signals. A possible selection criterion is based on discrimination conditions of frequency and time ranges. The appropriate analysis is performed on the basis of the extremal analysis enabling to select ranges corresponding to observed objects. Selected ranges are transformed into time functions to be analyzed by model-based method. Therewith the frequency analysis is performed on the assumption of linear frequency modulation of the signal observed. In its turn, the amplitude analysis is based on the passive location model. Parameters are selected either by Monte-Carlo method or by direct processing of equidistant grid nodes.

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34

BALUGIN, N. V., B. A. FOMIN, A. D. LYKOV, and V. A. YUSHKOV. "ESTIMATION OF STRATOSPHERIC AEROSOL EFFECTS ON STRATOSPHERIC RADIATION BUDGET ACCORDING TO OPTICAL BALLOON BACKSCATTER PROBE AND RADIATION MODELING." Meteorologiya i Gidrologiya, no. 10 (October 2022): 121–29. http://dx.doi.org/10.52002/0130-2906-2022-10-121-129.

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A method for evaluating stratospheric aerosol effects on the stratospheric radiation budget according to balloon sounding with an optical aerosol backscatter probe is presented. It is shown for the sounding in the equatorial zone under conditions of perturbed aerosol filling of the stratosphere that observed changes in the composition of stratospheric aerosol lead to significant changes (2-3-fold) in radiative heating. The evaluation technique is based on using the radiative (line-by-line and Monte Carlo) model of solar radiation transfer and can be especially useful in case of episodical perturbations of the stratospheric aerosol layer resulting from anthropogenic and natural disasters accompanied by aerosol emissions.

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35

Bolduc, David L., Vilmar Villa, David J. Sandgren, G. David Ledney, William F. Blakely, and Rolf Bünger. "Application of Multivariate Modeling for Radiation Injury Assessment: A Proof of Concept." Computational and Mathematical Methods in Medicine 2014 (2014): 1–17. http://dx.doi.org/10.1155/2014/685286.

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Multivariate radiation injury estimation algorithms were formulated for estimating severe hematopoietic acute radiation syndrome (H-ARS) injury (i.e., response category three or RC3) in a rhesus monkey total-body irradiation (TBI) model. Classical CBC and serum chemistry blood parameters were examined prior to irradiation (d 0) and on d 7, 10, 14, 21, and 25 after irradiation involving 24 nonhuman primates (NHP) (Macaca mulatta) given 6.5-Gy60CoΥ-rays (0.4 Gy min−1) TBI. A correlation matrix was formulated with the RC3 severity level designated as the “dependent variable” and independent variables down selected based on their radioresponsiveness and relatively low multicollinearity using stepwise-linear regression analyses. Final candidate independent variables included CBC counts (absolute number of neutrophils, lymphocytes, and platelets) in formulating the “CBC” RC3 estimation algorithm. Additionally, the formulation of a diagnostic CBC and serum chemistry “CBC-SCHEM” RC3 algorithm expanded upon the CBC algorithm model with the addition of hematocrit and the serum enzyme levels of aspartate aminotransferase, creatine kinase, and lactate dehydrogenase. Both algorithms estimated RC3 with over 90% predictive power. Only the CBC-SCHEM RC3 algorithm, however, met the critical three assumptions of linear least squares demonstrating slightly greater precision for radiation injury estimation, but with significantly decreased prediction error indicating increased statistical robustness.

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Muneer, T., M. S. Gul, and J. Kubie. "Models for Estimating Solar Radiation and Illuminance From Meteorological Parameters." Journal of Solar Energy Engineering 122, no. 3 (July 1, 2000): 146–53. http://dx.doi.org/10.1115/1.1313529.

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Sunshine fraction, cloud amount, temperature, and global irradiation are the most commonly measured meteorological parameters. In this article five models based mainly on the abovementioned variables for the determination of irradiation and illuminance components are presented. These models are divided into three categories. Category 1 includes three solar radiation models: a Meteorological Radiation Model (MRM), developed by present authors based on sunshine fraction and temperature data, b Cloud-Cover Radiation Model (CRM)—modification of an earlier model for the UK by the present authors based on cloud-cover in oktas, and c Page Radiation Model (PRM), developed by Page based on simultaneous sunshine and cloud data. Category 2 comprises of a new Diffuse Ratio Model (DRM), developed by authors, for estimating diffuse irradiation when global irradiation is provided as the input parameter. The third category includes luminous efficacy models that enable estimation of diffuse and global illuminance once the respective irradiation components have been obtained from category 1 models. [S0199-6231(00)02003-7]

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37

Grant, R. H., and J. R. Slusser. "Estimation of Ultraviolet-A Irradiance from Measurements of 368-nm Spectral Irradiance." Journal of Atmospheric and Oceanic Technology 22, no. 12 (December 1, 2005): 1853–63. http://dx.doi.org/10.1175/jtech1823.1.

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Abstract The estimation of ultraviolet-A (UV-A) radiation across the earth’s surface is needed to model plant productivity and future impacts of ultraviolet-B radiation on plant productivity. We have developed two models to estimate the UV-A irradiance from measurements of the diffuse and global spectral irradiance at 368 nm. The models were developed from 30-min-interval measurements made throughout 2000 at three locations across the United States and evaluated from 30-min measurements made throughout 2000 at three additional locations and throughout 2001 and 2002 at seven locations. UV-A irradiance was best estimated from measured global 368-nm irradiance and empirical functions defining the UV-A and 368-nm irradiance values estimated from a theoretical pseudospherical two-stream discrete-ordinates radiative transfer model. The radiative transfer model provided baseline irradiance relationships between UV-A irradiance and 368-nm spectral irradiance. The semiempirical model estimated the UV-A irradiance at seven locations across the United States with a mean bias error of 0.5 W m−2 and a root-mean-square error of 2 W m−2, corresponding to approximately ±4% of a clear-sky irradiance of 50 W m−2 for a solar zenith angle of 30°. This model error was comparable to the combined effect of previously estimated UV-A and 368-nm irradiance measurement errors.

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38

O. Akpootu, Davidson, Bello I. Tijjani, and Usman M. Gana. "Empirical models for predicting global solar radiation using meteorological parameters for Sokoto, Nigeria." International Journal of Physical Research 7, no. 2 (July 22, 2019): 48. http://dx.doi.org/10.14419/ijpr.v7i2.29160.

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The performances of sunshine, temperature and multivariate models for the estimation of global solar radiation for Sokoto (Latitude 13.020N, Longitude 05.250E and 350.8 m asl) located in the Sahelian region in Nigeria were evaluated using measured monthly average daily global solar radiation, maximum and minimum temperatures, sunshine hours, rainfall, wind speed, cloud cover and relative humidity meteorological data during the period of thirty one years (1980-2010). The comparison assessment of the models was carried out using statistical indices of coefficient of determination (R2), Mean Bias Error (MBE), Root Mean Square Error (RMSE), Mean Percentage Error (MPE), t – test, Nash – Sutcliffe Equation (NSE) and Index of Agreement (IA). For the sunshine based models, a total of ten (10) models were developed, nine (9) existing and one author’s sunshine based model. For the temperature based models, a total of four (4) models were developed, three (3) existing and one author’s temperature based model. The results of the existing and newly developed author’s sunshine and temperature based models were compared and the best empirical model was identified and recommended. The results indicated that the author’s quadratic sunshine based model involving the latitude and the exponent temperature based models are found more suitable for global solar radiation estimation in Sokoto. The evaluated existing Ångström type sunshine based model for the location was compared with those available in literature from other studies and was found more suitable for estimating global solar radiation. Comparing the most suitable sunshine and temperature based models revealed that the temperature based models is more appropriate in the location. The developed multivariate regression models are found suitable as evaluation depends on the available combination of the meteorological parameters based on two to six variable correlations. The recommended models are found suitable for estimating global solar radiation in Sokoto and regions with similar climatic information with higher accuracy and climatic variability.

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39

Yang, Qiang, and Yuanqing Zheng. "Model-based Head Orientation Estimation for Smart Devices." Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 5, no. 3 (September 9, 2021): 1–24. http://dx.doi.org/10.1145/3478089.

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Voice interaction is friendly and convenient for users. Smart devices such as Amazon Echo allow users to interact with them by voice commands and become increasingly popular in our daily life. In recent years, research works focus on using the microphone array built in smart devices to localize the user's position, which adds additional context information to voice commands. In contrast, few works explore the user's head orientation, which also contains useful context information. For example, when a user says, "turn on the light", the head orientation could infer which light the user is referring to. Existing model-based works require a large number of microphone arrays to form an array network, while machine learning-based approaches need laborious data collection and training workload. The high deployment/usage cost of these methods is unfriendly to users. In this paper, we propose HOE, a model-based system that enables Head Orientation Estimation for smart devices with only two microphone arrays, which requires a lower training overhead than previous approaches. HOE first estimates the user's head orientation candidates by measuring the voice energy radiation pattern. Then, the voice frequency radiation pattern is leveraged to obtain the final result. Real-world experiments are conducted, and the results show that HOE can achieve a median estimation error of 23 degrees. To the best of our knowledge, HOE is the first model-based attempt to estimate the head orientation by only two microphone arrays without the arduous data training overhead.

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40

ISLAMI, MUHAMMAD IRFAN, NAZLI ISMAIL, ISMAIL ISMAIL, and DEA RIMASILANA. "Empirical model for the estimation of global solar radiation in the Aceh Besar Regency, Aceh." Jurnal Natural 23, no. 1 (March 12, 2023): 28–34. http://dx.doi.org/10.24815/jn.v23i1.28697.

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Solar energy plays an important role in the temperature distribution on the Earth's surface and essential energy that sustains life for human. In the calculation of solar energy, the limitation of solar radiation data is a major obstacle. Solar radiation data is very limited at some observation stations due to the costly procurement of measuring instruments and complicated techniques. Estimation of global solar radiation using empirical models is one way to overcome the limitations of global solar radiation data at various locations. This study built the Angstrom-Prescott model to estimate global solar radiation based on the sunshine duration’s parameter in Aceh Besar Regency. Two years (2019-2020) global solar radiation and sunshine duration data from Aceh Climatological Station were used to estimate global solar radiation in 2021. Data for 2021 was using to evaluated the equation H/H0=0.28+0.22 (n/N), the results showed good model accuracy with an RMSE value of 0.052 and a MAPE of 11% (good forecasting). The model equation has been reliable to calculate solar radiation in four locations in Aceh Besar Regency.

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M. TAHASHILDAR, PRADIP K. BORA, LALA I. P. RAY, and D. THAKURIA. "Comparison of different reference evapotranspiration (ET0) models and determination of crop-coefficients of french bean (Phesiolus vulgaris.) in mid hill region of Meghalaya." Journal of Agrometeorology 19, no. 3 (September 1, 2017): 233–37. http://dx.doi.org/10.54386/jam.v19i3.645.

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The water requirement and crop evapotranspiration (ETc)is determined using reference evapotranspiration (ET0) and crop-coefficient (kc). Numerous models are available for estimation of ET0,among which Penman-Monteith (FAO-56) model is considered to be the most accurate and universally acceptable. In present study eight models for estimation of ET0viz. Modified Penman method, Hargreaves equation, Samani-Hargreaves equation, Thornthwaite equation, Solar radiation method, Net radiation method, Blaney-Criddle method and Radiation method were compared with Penman-Monteith model to find out the accuracy of prediction with limited weather parameters. Among these, Net radiation and Solar radiation models were found to yield relatively closer values. A field experiment was also conducted withfrench bean (Phesiolus vulgaris.) crop in UMS-GmbH cylindrical field lysimeter of 30 cm diameter and 120 cm deep for determination of crop coefficient taking Penman-Monteith FAO-56 model as the base model for ET0 estimation. The values of ETc as determined in field lysimeter varied from 3.80 mm-d-1 to 5.89 mm-d-1. The kc for initial, mid and maturity were found to be 0.45, 1.01 and 0.39, respectively.

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42

Salmi, Mohamed, Hassen Bouzgou, Yarub Al-Douri, and Abdelhakim Boursas. "Evaluation of the Hourly Global Solar Radiation on a Horizontal Plane for Two Sites in Algeria." Advanced Materials Research 925 (April 2014): 641–45. http://dx.doi.org/10.4028/www.scientific.net/amr.925.641.

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We present three models for the estimation of hourly global solar radiation for two sites in Algeria, namely: Djelfa (Latitude 34.68°N, Longitude 3.25°E, Altitude 1126 (m)) and Ain Bessem (Latitude 36.31°N, Longitude 3.67°E, Altitude 629 (m)). The models are: the Gaussian distribution model, the model by Collares-Pereira-RabI and the H.A. model (Hourly absolute modelling approach). The experimental assessment was done using recorded values of the hourly global solar radiation on a horizontal plane during the period 2000-2004. The obtained results show a close similarity between the solar radiation values calculated by the three models and the measured values, especially for the first model. The experimental validation shows promising results for the estimation and precise prediction of the hourly global solar radiation.

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43

LACERDA, ZILDA C. DE, and JOSÉ E. P. TURCO. "Estimation methods of reference evapotranspiration (ETo) for Uberlândia -MG." Engenharia Agrícola 35, no. 1 (February 2015): 27–38. http://dx.doi.org/10.1590/1809-4430-eng.agric.v35n1p27-38/2015.

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One approach to verify the adequacy of estimation methods of reference evapotranspiration is the comparison with the Penman-Monteith method, recommended by the United Nations of Food and Agriculture Organization - FAO, as the standard method for estimating ET0. This study aimed to compare methods for estimating ET0, Makkink (MK), Hargreaves (HG) and Solar Radiation (RS), with Penman-Monteith (PM). For this purpose, we used daily data of global solar radiation, air temperature, relative humidity and wind speed for the year 2010, obtained through the automatic meteorological station, with latitude 18° 91' 66" S, longitude 48° 25' 05" W and altitude of 869m, at the National Institute of Meteorology situated in the Campus of Federal University of Uberlandia - MG, Brazil. Analysis of results for the period were carried out in daily basis, using regression analysis and considering the linear model y = ax, where the dependent variable was the method of Penman-Monteith and the independent, the estimation of ET0 by evaluated methods. Methodology was used to check the influence of standard deviation of daily ET0 in comparison of methods. The evaluation indicated that methods of Solar Radiation and Penman-Monteith cannot be compared, yet the method of Hargreaves indicates the most efficient adjustment to estimate ETo.

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Musselman, K. N., and J. W. Pomeroy. "Estimation of Needleleaf Canopy and Trunk Temperatures and Longwave Contribution to Melting Snow." Journal of Hydrometeorology 18, no. 2 (February 1, 2017): 555–72. http://dx.doi.org/10.1175/jhm-d-16-0111.1.

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AbstractA measurement and modeling campaign evaluated variations in tree temperatures with solar exposure at the edge of a forest clearing and how the resulting longwave radiation contributed to spatial patterns of snowmelt energy surrounding an individual tree. Compared to measurements, both a one-dimensional (1D) energy-balance model and a two-dimensional (2D) radial trunk heat transfer model that simulated trunk surface temperatures and thermal inertia performed well (RMSE and biases better than 1.7° and ±0.4°C). The 2D model that resolved a thin bark layer better simulated daytime temperature spikes. Measurements and models agreed that trunk surfaces returned to ambient air temperature values near sunset. Canopy needle temperatures modeled with a 1D energy-balance approach were within the range of measurements. The radiative transfer model simulated substantial tree-contributed snow surface longwave irradiance to a distance of approximately one-half the tree height, with higher values on the sun-exposed sides of the tree. Trunks had very localized and substantially lower longwave energy influence on snowmelt compared to that of the canopy. The temperature and radiative transfer models provide the spatially detailed information needed to develop scaling relationships for estimating net radiation for snowmelt in sparse and discontinuous forest canopies.

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45

Wu, Dongya, Huanzhang Lu, Bendong Zhao, Junliang Liu, and Ming Zhao. "Micro-Motion Dynamics and Shape Parameters Estimation Based on an Infrared Signature Model of Spatial Targets." Electronics 8, no. 7 (July 4, 2019): 755. http://dx.doi.org/10.3390/electronics8070755.

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Infrared imaging is widely applied in the discrimination of spatial targets. Extracting distinguishable features from the infrared signature of spatial targets is an important premise for this task. When a target in outer space experiences micro-motion, it causes periodic fluctuations in the observed infrared radiation intensity signature. Periodic fluctuations can reflect some potential factors of the received data, such as structure, dynamics, etc., and provide possible ways to analyze the signature. The purpose of this paper is to estimate the micro-motion dynamics and geometry parameters from the observed infrared radiation intensity signature. To this end, we have studied the signal model of the infrared radiation intensity signature, conducted the geometry and micro-motion models of the target, and we proposed a joint parameter estimation method based on optimization techniques. After analyzing the estimation results, we testified that the parameters of micro-motion and geometrical shape of the spatial target can be effectively estimated by our estimation method.

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46

Salisu, S. "NEW MODEL FOR SOLAR RADIATION ESTIMATION FROM MEASURED AIR TEMPERATURE AND RELATIVE HUMIDITY IN NIGERIA." Nigerian Journal of Technology 36, no. 3 (June 30, 2017): 917–22. http://dx.doi.org/10.4314/njt.v36i3.35.

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Solar radiation prediction is essential for effective and reliable solar power project, predicted solar radiation can be used for accurate solar energy prediction. Solar radiation measurement is not sufficient in Nigeria for various reasons such as maintenance and repair cost, calibration of instrument, and expansive of measuring device. In this paper, adaptive neuro-fuzzy inference system (ANFIS) model was developed to predict the monthly average solar radiation in Nigeria. Air temperature of monthly mean minimum temperature, maximum temperature and relative humidity obtained from Nigerian Meteorological Agency (NIMET) were used as inputs to the ANFIS model and monthly mean global solar radiation was used as out of the model. Statistical evaluation of the model was done based on root mean square error (RMSE) and correlation coefficient R to examine the accuracy of the developed model. The values of RMSE and R for the training data are 0.91315MJ/m2 and 0.91264MJ/m2 respectively. The obtained result showed a good correlation between the predicted and measured solar radiation which proves ANFIS to be a good model for solar radiation prediction.Â Â http://dx.doi.org/10.4314/njt.v36i3.35

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47

Okundamiya, Michael S., and Israel E. Okpamen. "A Linear Regression Model for Global Solar Radiation on Horizontal Surfaces at Warri, Nigeria." International Journal of Renewable Energy Development 2, no. 3 (October 30, 2013): 121–26. http://dx.doi.org/10.14710/ijred.2.3.121-126.

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The growing anxiety on the negative effects of fossil fuels on the environment and the global emission reduction targets call for a more extensive use of renewable energy alternatives. Efficient solar energy utilization is an essential solution to the high atmospheric pollution caused by fossil fuel combustion. Global solar radiation (GSR) data, which are useful for the design and evaluation of solar energy conversion system, are not measured at the forty-five meteorological stations in Nigeria. The dearth of the measured solar radiation data calls for accurate estimation. This study proposed a temperature-based linear regression, for predicting the monthly average daily GSR on horizontal surfaces, at Warri (latitude 5.020N and longitude 7.880E) an oil city located in the south-south geopolitical zone, in Nigeria. The proposed model is analyzed based on five statistical indicators (coefficient of correlation, coefficient of determination, mean bias error, root mean square error, and t-statistic), and compared with the existing sunshine-based model for the same study. The results indicate that the proposed temperature-based linear regression model could replace the existing sunshine-based model for generating global solar radiation data. Keywords: air temperature; empirical model; global solar radiation; regression analysis; renewable energy; Warri

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48

Jenblat, S. S., and O. V. Volkova. "Estimation of multi-layer coating efficiency for passive radiative cooling." Omsk Scientific Bulletin. Series Aviation-Rocket and Power Engineering 5, no. 2 (2021): 37–46. http://dx.doi.org/10.25206/2588-0373-2021-5-2-37-46.

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Passive radiative cooling is a promising direction in energy conservation and environmental protection. One of the ways to increase the efficiency of radiative cooling systems is the use of multi-layer coatings. In recent years, several novel materials with high emissivity have been proposed, which allow the creation of radiators that provide an average daily cooling power of approximately 100 W/m2 during daytime. Based on the developed mathematical model, the optical properties of the multi-layer coating for the radiative cooling system were evaluated by the Transfer Matrix Method and the effectiveness of radiative cooling was determined due to the use of the multi-layer coating in the climatic conditions of Syria (Latakia). The results of modeling the atmospheric transmittance in the summer months in Syria (Latakia) are presented. The developed mathematical model, methods for modeling atmospheric transmittance, calculating solar radiation, and evaluating the optical properties of multi-layer coating, allow determining an effective multi-layer coating for radiative cooling systems in any climatic conditions

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Chernikova, Oksana Sergeevna, and Yuliya Sergeevna Chetvertakova. "Two-stage parametric identification procedure to predict satellite orbital motion." International Journal of Electrical and Computer Engineering (IJECE) 12, no. 5 (October 1, 2022): 5348. http://dx.doi.org/10.11591/ijece.v12i5.pp5348-5354.

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<span>The paper presents a new step-by-step procedure for constructing a navigation satellite motion model. At the first stage of the procedure, the parameters of the radiation pressure model are estimated using the maximum likelihood method. The statistic estimator based on the continuous-discrete adaptive unscented Kalman filter is proposed for the solar radiation model parameters estimation. Step-by-step scheme of filtering algorithm used for the software development are given. At the second stage, the parameters of the unaccounted perturbations model are estimated based on the results of residual differences measurements. The obtained results lead to signiﬁcant improvement of prediction quality of the satellite trajectory.</span>

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50

Taha, Ahmed Tawfik Hussein. "ESTIMATION OF HOURLY GLOBAL SOLAR RADIATION IN EGYPT USING MATHEMATICAL MODEL." Misr Journal of Agricultural Engineering 27, no. 4 (October 1, 2010): 2033–47. http://dx.doi.org/10.21608/mjae.2010.105401.

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