Comparative Study of Artificial Neural Networks and Wavelet Artificial Neural Networks for Groundwater Depth Data Forecasting with Various Curve Fractal Dimensions

Water Resources Management

Volumn 28, Issue 15, 2014, Pages 5297-5317

  He, Zhenfang ^a,b,c   Zhang, Yaonan ^a   Guo, Qingchun ^c,d   Zhao, Xueru ^a,e  

^a Chinese Academy of Sciences   (China)

^b LIAOCHENG UNIVERSITY   (China)

^c UNIVERSITY OF CHINESE ACADEMY OF SCIENCES   (China)

^d Shaanxi Radio and TV University   (China)

^e LANZHOU UNIVERSITY   (China)

Author keywords

Artificial neural network; Fractal dimension; Groundwater depth; Mallat decomposition algorithm; Training algorithms; Wavelet artificial neural network

Indexed keywords

FORECASTING; FRACTAL DIMENSION; GROUNDWATER; GROUNDWATER RESOURCES; TIME SERIES; WAVELET DECOMPOSITION;

BAYESIAN REGULARIZATION ALGORITHMS; COMPARATIVE STUDIES; GROUND WATER DEPTHS; MALLAT DECOMPOSITION; PREDICTION ERRORS; RANDOM COMPONENTS; TIME SERIES PREDICTION; TRAINING ALGORITHMS;

NEURAL NETWORKS;

ALGORITHM; ARTIFICIAL NEURAL NETWORK; COMPARATIVE STUDY; DECOMPOSITION ANALYSIS; FORECASTING METHOD; GROUNDWATER; TIME SERIES; WATER DEPTH; WAVELET ANALYSIS;

CHINA; GANZHOU; JIANGXI;

EID: 84918516098     PISSN: 09204741     EISSN: 15731650     Source Type: Journal    
DOI: 10.1007/s11269-014-0802-0     Document Type: Article

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