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DOI	10.1007/s00704-019-02982-x
	Ensemble gene expression programming: a new approach for evolution of parsimonious streamflow forecasting model
	Rahmani-Rezaeieh, Aidin 1; Mohammadi, Mirali 1,2; Danandeh Mehr, Ali 3
通讯作者	Mohammadi, Mirali
来源期刊	THEORETICAL AND APPLIED CLIMATOLOGY
ISSN	0177-798X
EISSN	1434-4483
出版年	2020
卷号	139 期号:1-2 页码:549-564
英文摘要	A precise forecast of streamflow in intermittent rivers is of major difficulties and challenges in watershed management, particularly in arid and semiarid regions. The present research study introduces an ensemble gene expression programming (EGEP) modeling approach to 1- and 2-day ahead streamflow forecasts that meet both accuracy and simplicity criteria of an applied model. Three main components of the proposed EGEP approach which are capable of producing a parsimonious model include (i) creating a population of suitable solutions using classic genetic programming (GP) instead of a single solution, (ii) combining the solutions throughout gene expression programming, and (iii) parsimony selection based upon trade-off analysis between the complexity and accuracy of the best-evolved solutions at the holdout validation set. The EGEP model was trained and verified using the streamflow measurements from the Shahrchay River lying northwest of Iran. Several statistical indicators were computed for verification of the ensemble models' accuracy with that of classic GP and artificial neural network models developed as the benchmarks. Our results revealed that the EGEP outperforms the benchmarks. It is an explicit, simple, and precise approach and, therefore, worthy to be used in practice.
类型	Article
语种	英语
国家	Iran ; Turkey
收录类别	SCI-E
WOS记录号	WOS:000511515200037
WOS关键词	ARTIFICIAL-INTELLIGENCE METHODS ; NEURAL-NETWORKS ; WAVELET ; PERFORMANCE ; PREDICTION ; PARADIGM ; ANN
WOS类目	Meteorology & Atmospheric Sciences
WOS研究方向	Meteorology & Atmospheric Sciences
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/315652
作者单位	1.Islamic Azad Univ, Dept Civil Engn, Najafabad Branch, Najafabad, Iran; 2.Urmia Univ, Fac Engn, Dept Civil Engn, POB 165, Orumiyeh, Iran; 3.Antalya Bilim Univ, Dept Civil Engn, Antalya, Turkey
推荐引用方式 GB/T 7714	Rahmani-Rezaeieh, Aidin,Mohammadi, Mirali,Danandeh Mehr, Ali. Ensemble gene expression programming: a new approach for evolution of parsimonious streamflow forecasting model[J],2020,139(1-2):549-564.
APA	Rahmani-Rezaeieh, Aidin,Mohammadi, Mirali,&Danandeh Mehr, Ali.(2020).Ensemble gene expression programming: a new approach for evolution of parsimonious streamflow forecasting model.THEORETICAL AND APPLIED CLIMATOLOGY,139(1-2),549-564.
MLA	Rahmani-Rezaeieh, Aidin,et al."Ensemble gene expression programming: a new approach for evolution of parsimonious streamflow forecasting model".THEORETICAL AND APPLIED CLIMATOLOGY 139.1-2(2020):549-564.