Arid
DOI10.1016/j.jhydrol.2018.05.030
Markov chain-incorporated and synthetic data-supported conditional artificial neural network models for forecasting monthly precipitation in arid regions
Aksoy, Hafzullah1; Dahamsheh, Ahmad2
通讯作者Aksoy, Hafzullah
来源期刊JOURNAL OF HYDROLOGY
ISSN0022-1694
EISSN1879-2707
出版年2018
卷号562页码:758-779
英文摘要

For forecasting monthly precipitation in an arid region, the feed forward back-propagation, radial basis function and generalized regression artificial neural networks (ANNs) are used in this study. The ANN models are improved after incorporation of a Markov chain-based algorithm (MC-ANNs) with which the percentage of dry months is forecasted perfectly, thus generation of any non-physical negative precipitation is eliminated. Due to the fact that recorded precipitation time series are usually shorter than the length needed for a proper calibration of ANN models, synthetic monthly precipitation data are generated by Thomas-Fiering model to further improve the performance of forecasting. For case studies from Jordan, it is seen that only a slightly better performance is achieved with the use of MC and synthetic data. A conditional statement is, therefore, established and imbedded into the ANN models after the incorporation of MC and support of synthetic data, to substantially improve the ability of the models for forecasting monthly precipitation in arid regions.


英文关键词Arid region Artificial neural networks Intermittent precipitation Markov chain Synthetic data Thomas-Fiering model
类型Article
语种英语
国家Turkey ; Jordan
收录类别SCI-E
WOS记录号WOS:000438003000059
WOS关键词MONTHLY RAINFALL ; TIME-SERIES ; EVAPOTRANSPIRATION ; PREDICTION ; FLOW ; JORDAN
WOS类目Engineering, Civil ; Geosciences, Multidisciplinary ; Water Resources
WOS研究方向Engineering ; Geology ; Water Resources
资源类型期刊论文
条目标识符http://119.78.100.177/qdio/handle/2XILL650/211066
作者单位1.Istanbul Tech Univ, Dept Civil Engn, TR-34469 Istanbul, Turkey;
2.Al Hussein Bin Talal Univ, Dept Civil Engn, Maan, Jordan
推荐引用方式
GB/T 7714
Aksoy, Hafzullah,Dahamsheh, Ahmad. Markov chain-incorporated and synthetic data-supported conditional artificial neural network models for forecasting monthly precipitation in arid regions[J],2018,562:758-779.
APA Aksoy, Hafzullah,&Dahamsheh, Ahmad.(2018).Markov chain-incorporated and synthetic data-supported conditional artificial neural network models for forecasting monthly precipitation in arid regions.JOURNAL OF HYDROLOGY,562,758-779.
MLA Aksoy, Hafzullah,et al."Markov chain-incorporated and synthetic data-supported conditional artificial neural network models for forecasting monthly precipitation in arid regions".JOURNAL OF HYDROLOGY 562(2018):758-779.
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