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博士生邹玲发表会议论文MONTHLY MEAN GLOBAL SOLAR RADIATION MODELING USING ARTIFICIAL NEURAL NETWORK TECHNIQUE IN
发布时间:2017-03-17     发布者:yz         审核者:     浏览次数:

标题:MONTHLY MEAN GLOBAL SOLAR RADIATION MODELING USING ARTIFICIAL NEURAL NETWORK TECHNIQUE IN SOUTHEAST HILL AREAS, CHINA DURING 1993-2013作者:Zou, Ling; Lin, Ai-Wen; Wang, Lun-Che; Yang, Qian; Zhao, Zhen-Zhen

来源出版物:ENERGY AND MECHANICAL ENGINEERING页码:394-401 出版年:2016

会议名称:International Conference on Energy and Mechanical Engineering (EME)

会议时间:OCT 17-18, 2015

会议地点:Wuhan, PEOPLES R CHINA

摘要:An artificial neural network (ANN) daily measured global solar radiation and meteorological data (temperature, precipitation, relatively humidity, air pressure, sunshine duration, maximum temperature and minimum temperature) from 1993 to 2013, and geographical date (latitude, longitude and altitude) in 16 stations are used to estimate the mean monthly global solar radiation in southeast hill areas of China. Global solar radiation data from 10 stations are used for training the artificial neural network and data from 4 stations are applied to validate the artificial neural network and the remaining two stations are employed to test it. 13 combinations of input variables are considered and the performance of the models is evaluated by root mean square error (RMSE) and mean bias error (MBE). The monthly mean global solar radiation estimations by 13 ANN models are in good agreement with the measured values (R>0.86, RMSE

入藏号:WOS:000394749400046

文献类型:Proceedings Paper

语种:English

作者关键词:Global solar radiation, Artificial neural network, Radiation modeling

扩展关键词:METEOROLOGICAL DATA

通讯作者地址:Zou, L (reprint author), Wuhan Univ, Sch Resource & Environm Sci, Wuhan 430079, Hubei, Peoples R China.

电子邮件地址:cheryl_zou@whu.edu.cn

地址:

[Zou, Ling; Lin, Ai-Wen; Yang, Qian; Zhao, Zhen-Zhen] Wuhan Univ, Sch Resource & Environm Sci, Wuhan 430079, Hubei, Peoples R China.

[Wang, Lun-Che] China Univ Geosci, Dept Geog, Sch Earth Sci, Wuhan 430074, Hubei, Peoples R China.

[Wang, Lun-Che] China Univ Geosci, State Key Lab Biogeol & Environm Geol, Wuhan 430074, Hubei, Peoples R China.

研究方向:Energy & Fuels; Engineering

ISBN:978-981-4749-49-7