Comparison of artificial intelligence methods and empirical equations to estimate daily solar radiation

Mehdizadeh, Saeid; Behmanesh, Javad; Khalili, Keivan

doi:10.1016/j.jastp.2016.06.006

Cited by 60 publications

(17 citation statements)

References 51 publications

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“…Changes in the amount of greatly influence the hydrological cycle, terrestrial ecological systems, and the climate [2]. Complete and accurate data at a specific region are highly crucial to regional crop growth modeling, evapotranspiration estimation, irrigation system development, and utilization of solar energy resources.…”

Section: Introductionmentioning

confidence: 99%

Comparative Analysis of Global Solar Radiation Models in Different Regions of China

Zhang

Cui

Feng

et al. 2018

Advances in Meteorology

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Complete and accurate global solar radiation ( ) data at a specific region are crucial for regional climate assessment and crop growth modeling. The objective of this paper was to evaluate the capability of 12 solar radiation models based on meteorological data obtained from 21 meteorological stations in China. The results showed that the estimated and measured daily had statistically significant correlations ( < 0.01) for all the 12 models in 7 subzones of China. The Bahel model showed the best performance for daily estimation among the sunshine-based models, with average 2 of 0. , and average NS of 0.696, respectively. On monthly scale,Ögelman model showed the best performance among the sunshine-based models, with average RE of 5.66%. The BC model showed the best performance among the temperature-based models, with average RE of 8.26%. Generally, the sunshine-based models were more accurate than the temperature-based models. Overall, the Bahel model is recommended to estimate daily ,Ögelman model is recommended to estimate monthly average daily in China when the sunshine duration is available, and the BC model is recommended to estimate both daily and monthly average daily when only temperature data are available.

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Section: Introductionmentioning

confidence: 99%

Comparative Analysis of Global Solar Radiation Models in Different Regions of China

Zhang

Cui

Feng

et al. 2018

Advances in Meteorology

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“…The artificial intelligence approach has been utilized by some researchers to predict the global solar radiation [22,[34][35][36][37]. However, more factors are involved in the artificial intelligence techniques compared to empirical models.…”

Section: Artificial Intelligence Approachmentioning

confidence: 99%

Solar Radiation Parameters for Assessing Temperature Distributions on Bridge Cross-Sections

et al. 2018

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Solar radiation is one of the most important factors influencing the temperature distribution on bridge girder cross-sections. The bridge temperature distribution can be estimated using estimation models that incorporate solar radiation data; however, such data could be cost-or time-prohibitive to obtain. A review of literature was carried out on estimation models for solar radiation parameters, including the global solar radiation, beam solar radiation and diffuse solar radiation. Solar radiation data from eight cities in Fujian Province in southeastern China were obtained on site. Solar radiation models applicable to Fujian, China were proposed and verified using the measured data. The linear Ångström-Page model (based on sunshine duration) can be used to estimate the daily global solar radiation. The Collares-Pereira and Rabl model and the Hottel model can be used to estimate the hourly global solar radiation and the beam solar radiation, respectively. Three bridges were chosen as case study, for which the temperature distribution on girder cross-sections were monitored on site. Finite element models (FEM) of cross-sections of bridge girders were implemented using the Midas program. The temperature-time curves obtained from FEM showed very close agreement with the measured values for summertime. Ignoring the solar radiation effect would result in lower and delayed temperature peaks. However, the influence of solar radiation on the temperature distribution in winter is negligible.

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“…A sınıfı buharlaşma tavası, lizimetre gibi aletlerle doğrudan ölçülebilen buharlaşma; su dengesi, kütle transferi, enerji dengesi gibi metotlar veya geliştirilen çeşitli ampirik denklemler yardımıyla dolaylı olarak hesaplanabilir. Bununla birlikte son yıllarda, hidrolojik ve meteorolojik parametrelerin tahmin edilmesinde yaygın olarak kullanılan yapay zekâ metotları ile de buharlaşma tahmini yapılmaktadır [1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16].…”

Section: Introductionunclassified

Aylik Buharlaşma Tahmi̇ni̇nde Yapay Zeka Yöntemleri̇ni̇n Kullanilabi̇li̇rli̇ği̇

Ozel¹,

Büyükyıldız²

2019

Ömer Halisdemir Üniversitesi Mühendislik Bilimleri Dergisi

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Comparison of artificial intelligence methods and empirical equations to estimate daily solar radiation

Cited by 60 publications

References 51 publications

Comparative Analysis of Global Solar Radiation Models in Different Regions of China

Comparative Analysis of Global Solar Radiation Models in Different Regions of China

Solar Radiation Parameters for Assessing Temperature Distributions on Bridge Cross-Sections

Aylik Buharlaşma Tahmi̇ni̇nde Yapay Zeka Yöntemleri̇ni̇n Kullanilabi̇li̇rli̇ği̇

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