干旱区生态环境知识资源中心(Arid): Enhancing Accuracy of Forecasting Monthly Reservoir Inflow by Using Comparison of Three New Hybrid Models: A Case Study of The Droodzan Dam in Iran

Arid

DOI	10.1007/s40996-024-01418-5
	Enhancing Accuracy of Forecasting Monthly Reservoir Inflow by Using Comparison of Three New Hybrid Models: A Case Study of The Droodzan Dam in Iran
	Khorram, Saeed; Jehbez, Nima
通讯作者	Khorram, S
来源期刊	IRANIAN JOURNAL OF SCIENCE AND TECHNOLOGY-TRANSACTIONS OF CIVIL ENGINEERING
ISSN	2228-6160
EISSN	2364-1843
出版年	2024
英文摘要	Predicting the reservoir inflows plays a central role in the control and management of water resources and the related activities, such as the reservoir exploitation and flood/drought control. The complex nature of the hydrological systems and difficulties in their application processes have urged the researchers to look for more efficient reservoir-inflow modeling methods. Aimed at this objective, the current study developed three SVM-GA, ANFIS-GA and ARIMA-LSTM hybrid models, compared their performances with one another as well as with LSTM, SVM, ANFIS and ARIMA models and SWAT hydrological model in predicting the inflows to the Droodzan Dam reservoir in Fars Province, Iran, and evaluated their results using such statistical criteria as the RMSE, MAE, MAPE, MSE and R2. In short, the results revealed that the combined methods performed better than the single models and ARIMA-LSTM and LSTM predicted the monthly reservoir inflows more accurately (R2 = 0.9272, 0.8805, training, and R2 = 0.9097, 0.8148, testing). Among the three combined and four single studied models, ARIMA-LSTM showed higher accuracy and had better potential in predicting the monthly reservoir inflows in arid and semi-arid regions.
英文关键词	Reservoir inflow forecasting Long short-term memory Support vector machines Artificial neural Fuzzy inference system Hybrid model
类型	Article ; Early Access
语种	英语
收录类别	SCI-E
WOS记录号	WOS:001201308800002
WOS关键词	SUPPORT VECTOR MACHINES ; DATA-DRIVEN MODELS ; RIVER-BASIN ; ARIMA
WOS类目	Engineering, Civil
WOS研究方向	Engineering
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/404280
推荐引用方式 GB/T 7714	Khorram, Saeed,Jehbez, Nima. Enhancing Accuracy of Forecasting Monthly Reservoir Inflow by Using Comparison of Three New Hybrid Models: A Case Study of The Droodzan Dam in Iran[J],2024.
APA	Khorram, Saeed,&Jehbez, Nima.(2024).Enhancing Accuracy of Forecasting Monthly Reservoir Inflow by Using Comparison of Three New Hybrid Models: A Case Study of The Droodzan Dam in Iran.IRANIAN JOURNAL OF SCIENCE AND TECHNOLOGY-TRANSACTIONS OF CIVIL ENGINEERING.
MLA	Khorram, Saeed,et al."Enhancing Accuracy of Forecasting Monthly Reservoir Inflow by Using Comparison of Three New Hybrid Models: A Case Study of The Droodzan Dam in Iran".IRANIAN JOURNAL OF SCIENCE AND TECHNOLOGY-TRANSACTIONS OF CIVIL ENGINEERING (2024).