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DOI	10.1080/19942060.2018.1560364
	Daily global solar radiation modeling using data-driven techniques and empirical equations in a semi-arid climate
	Samadianfard, Saeed 1; Majnooni-Heris, Abolfazl 1; Qasem, Sultan Noman 2,3; Kisi, Ozgur 4; Shamshirband, Shahaboddin 5,6; Chau, Kwok-wing 7
通讯作者	Shamshirband, Shahaboddin
来源期刊	ENGINEERING APPLICATIONS OF COMPUTATIONAL FLUID MECHANICS
ISSN	1994-2060
EISSN	1997-003X
出版年	2019
卷号	13 期号:1 页码:142-157
英文摘要	Solar radiation, moisture and temperature are the most vital meteorological variables which affect plant growth. Due to the fact that the global solar radiation (GSR) is scarcely gauged at meteorological stations in developing countries, it is commonly estimated by data-driven techniques or by empirical equations. In this study, support vector regression (SVR), model trees (MT), gene expression programming (GEP) and adaptive neuro-fuzzy inference system (ANFIS) and several empirical equations were applied to assess the relations between GSR and several meteorological variables including minimum temperature (T-min), maximum temperature (T-max), relative humidity (RH), sunshine hours (n), maximum sunshine hours (N), corrected clear-sky solar irradiation (ICSKY), day of year (DOY) and extra-terrestrial radiation (R-a). For this purpose, the daily GSR measured from the beginning of 2011 to the end of 2013 at Tabriz synoptic station, which is located in semi-arid regions of Iran, were used. A direct strong relationship was observed to exist between the GSR and n. For evaluating the performances of studied techniques, three different statistical indicators were used namely root mean square error (RMSE), mean absolute error (MAE), and correlation coefficient (CC). Additionally, a Taylor diagram was utilized to test the similarity between the observed and predicted GSR values. Results indicated that the SVR-6 with input parameters of R-a, RH, T-min, T-max, n/N had better accuracy in predicting GSR with RMSE of 1.656, MAE of 0.990, CC of 0.980 and WI of 0.990 than the other models. Moreover, MT-6 ranked as the second best model in the prediction of GSR values. As an interesting point, studied empirical equations had lower accuracies comparing with the SVR, GEP, MT and ANFIS methods. For instance, GSR values were computed by Angstrom and Prescott equation, as the best empirical equation, with RMSE of 1.786, MAE of 1.156, CC of 0.977 and WI of 0.988. Conclusively, results from the current study proved that the SVR provided reasonable trends for GSR modeling at Tabriz synoptic station. Furthermore, MT models with linear equations can be implemented with a high degree of simplicity and acceptable precision in GSR estimation.
英文关键词	Data-driven technics empirical equations meteorological parameters global solar radiation
类型	Article
语种	英语
国家	Iran ; Saudi Arabia ; Yemen ; Georgia ; Vietnam ; Peoples R China
开放获取类型	gold, Green Published
收录类别	SCI-E
WOS记录号	WOS:000454986900001
WOS关键词	ARTIFICIAL NEURAL-NETWORK ; SUPPORT VECTOR REGRESSION ; ABSOLUTE ERROR MAE ; INTELLIGENCE METHODS ; PREDICTION ; ANFIS ; ANN ; TEMPERATURE ; MANAGEMENT ; SYSTEMS
WOS类目	Engineering, Multidisciplinary ; Engineering, Mechanical ; Mechanics
WOS研究方向	Engineering ; Mechanics
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/215373
作者单位	1.Univ Tabriz, Fac Agr, Dept Water Engn, Tabriz, Iran; 2.Al Imam Mohammad Ibn Saud Islamic Univ IMSIU, Coll Comp & Informat Sci, Comp Sci Dept, Riyadh, Saudi Arabia; 3.Taiz Univ, Fac Appl Sci, Comp Sci Dept, Taizi, Yemen; 4.Ilia State Univ, Fac Nat Sci & Engn, Tbilisi, Georgia; 5.Ton Duc Thang Univ, Dept Management Sci & Technol Dev, Ho Chiminh City, Vietnam; 6.Ton Duc Thang Univ, Fac Informat Technol, Ho Chi Minh City, Vietnam; 7.Hong Kong Polytech Univ, Dept Civil & Environm Engn, Hong Kong, Peoples R China
推荐引用方式 GB/T 7714	Samadianfard, Saeed,Majnooni-Heris, Abolfazl,Qasem, Sultan Noman,et al. Daily global solar radiation modeling using data-driven techniques and empirical equations in a semi-arid climate[J],2019,13(1):142-157.
APA	Samadianfard, Saeed,Majnooni-Heris, Abolfazl,Qasem, Sultan Noman,Kisi, Ozgur,Shamshirband, Shahaboddin,&Chau, Kwok-wing.(2019).Daily global solar radiation modeling using data-driven techniques and empirical equations in a semi-arid climate.ENGINEERING APPLICATIONS OF COMPUTATIONAL FLUID MECHANICS,13(1),142-157.
MLA	Samadianfard, Saeed,et al."Daily global solar radiation modeling using data-driven techniques and empirical equations in a semi-arid climate".ENGINEERING APPLICATIONS OF COMPUTATIONAL FLUID MECHANICS 13.1(2019):142-157.