干旱区生态环境知识资源中心(Arid): Novel reliable model by integrating the adaptive neuro-fuzzy inference systems with wavelet transform and firefly algorithms for rainfall forecasting in the north of Iran

Arid

DOI	10.1007/s13201-022-01859-1
	Novel reliable model by integrating the adaptive neuro-fuzzy inference systems with wavelet transform and firefly algorithms for rainfall forecasting in the north of Iran
	Esmaeili, Farzad; Shabanlou, Saeid; Saadat, Mohsen
通讯作者	Shabanlou, S
来源期刊	APPLIED WATER SCIENCE
ISSN	2190-5487
EISSN	2190-5495
出版年	2023
卷号	13 期号:2
英文摘要	Rainfall is perhaps the most important source of drinking and agriculture water for the inhabitants of different parts of the world, particularly in arid and semi-arid area like Iran. Hence, the simulation of this hydrological phenomenon is crucial. The current research attempts to reproduce the long-term monthly precipitation of Ardabil, Iran, during 44 years from 1976 to 2020 for the first time via a hybrid fuzzy technique. For developing this model (WANFIS-FA), adaptive neuro-fuzzy inference system (ANFIS), firefly algorithm and wavelet transform were integrated. Firstly, the impacting lags of time series data were recognized by using the autocorrelation function and 14 WANFIS-FA models were defined using them. Then, the results of WANFIS-FA models were evaluated and the best WANFIS-FA model and the most influencing lags were found. For example, the variance accounted for index (VAF), correlation coefficient (R) and Nash-Sutcliffe coefficient (NSC) values for the superior WANFIS-FA model were computed to be 98.082, 0.990 and 0.980, respectively. In addition, the lags (t - 1), (t - 2), (t - 3) and (t - 12) were the most effective ones. Next, different members of the mother wavelet were tested and finally demy was selected as an optimal wavelet. Also, the analysis of the outcomes of the hybrid models demonstrated that the wavelet transform meaningfully enhanced the efficiency of the neuro-fuzzy model. Finally, the efficiency of WANFIS-FA was compared with ANFIS, WANFIS and ANFIS-FA, which displayed that WANFIS-FA performed better.
英文关键词	Rainfall Ardabil city ANFIS Firefly algorithm Wavelet transform Time series data
类型	Article
语种	英语
开放获取类型	gold
收录类别	SCI-E
WOS记录号	WOS:000906239300020
WOS关键词	HYBRID INTELLIGENT MODEL ; OPTIMIZATION ; ANFIS ; NETWORK
WOS类目	Water Resources
WOS研究方向	Water Resources
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/395398
推荐引用方式 GB/T 7714	Esmaeili, Farzad,Shabanlou, Saeid,Saadat, Mohsen. Novel reliable model by integrating the adaptive neuro-fuzzy inference systems with wavelet transform and firefly algorithms for rainfall forecasting in the north of Iran[J],2023,13(2).
APA	Esmaeili, Farzad,Shabanlou, Saeid,&Saadat, Mohsen.(2023).Novel reliable model by integrating the adaptive neuro-fuzzy inference systems with wavelet transform and firefly algorithms for rainfall forecasting in the north of Iran.APPLIED WATER SCIENCE,13(2).
MLA	Esmaeili, Farzad,et al."Novel reliable model by integrating the adaptive neuro-fuzzy inference systems with wavelet transform and firefly algorithms for rainfall forecasting in the north of Iran".APPLIED WATER SCIENCE 13.2(2023).