气候变化领域集成服务门户(CCPortal): Modelling hybrid and backpropagation adaptive neuro-fuzzy inference systems for flood forecasting

CCPortal

DOI	10.1007/s11069-021-04694-w
	Modelling hybrid and backpropagation adaptive neuro-fuzzy inference systems for flood forecasting
	Tabbussum R.; Dar A.Q.
发表日期	2021
ISSN	0921030X
起始页码	519
结束页码	566
卷号	108 期号:1
英文摘要	The ability of the adaptive neuro-fuzzy inference algorithm architecture to simulate floods is explored in this research. The development of models for flood forecasting has been centered on two adaptive neuro-fuzzy inference (ANFIS) algorithms. The Takagi–Sugeno fuzzy inference systems (FIS) generated through subtracted clustering were trained using hybrid and backpropagation training algorithms. Multiple statistical performance evaluators were used to assess the performability of the established models. The validity and predictive power of the models are evaluated by estimating a flood occurrence in the study area. In designing the models, a total of 12 inputs were employed. The best performability was found for the ANFIS model created utilizing a hybrid training algorithm with mean square error (MSE) of 0.00034, co-efficient of correlation (R2) of 97.066%, root mean square error (RMSE) of 0.018, Nash–Sutcliffe model efficiency (NSE) of 0.968, mean absolute error (MAE) of 0.0073 and combined accuracy (CA) of 0.018, indicating the possible usage of exploiting the established model for prediction of floods. © 2021, The Author(s), under exclusive licence to Springer Nature B.V.
关键词	Adaptive neuro-fuzzy inference system Backpropagation learning algorithm Gaussian membership function Hybrid learning algorithm Subtractive clustering Takagi–Sugeno fuzzy inference system
语种	英语
来源期刊	Natural Hazards
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/206595
作者单位	Department of Civil Engineering, National Institute of Technology Srinagar, Hazratbal, Srinagar, Jammu and Kashmir 190006, India
推荐引用方式 GB/T 7714	Tabbussum R.,Dar A.Q.. Modelling hybrid and backpropagation adaptive neuro-fuzzy inference systems for flood forecasting[J],2021,108(1).
APA	Tabbussum R.,&Dar A.Q..(2021).Modelling hybrid and backpropagation adaptive neuro-fuzzy inference systems for flood forecasting.Natural Hazards,108(1).
MLA	Tabbussum R.,et al."Modelling hybrid and backpropagation adaptive neuro-fuzzy inference systems for flood forecasting".Natural Hazards 108.1(2021).