NDLI: Research of sediment flux from Yellow River to the sea based on wavelet analysis and wavelet neural Network

Content Provider	IEEE Xplore Digital Library
Author	Zongwen Ma Xuegong Xu
Copyright Year	2010
Description	Author affiliation: College of Urban and Environmental Sciences, Peking University, Beijing 100871, China (Zongwen Ma; Xuegong Xu)
Abstract	Research on sediment flux from river to the sea is a frontier topic in Earth science worldwide. This paper analyzes the characteristics of annual sediment flux from Yellow River to the sea from 1950 to 2007, and presents a feasible approach to predict annual sediment flux. Methods used in this research include wavelet analysis and neural network. The results show that: (1) annual sediment flux variations from Yellow River to the sea have decline tendencies with an average decreasing rate of −20.09 million t/a between 1950 and 2007, and four catastrophe points detected are 1959, 1969, 1985 and 1997; (2) annual sediment flux series has the principal periods of 3–4 years, 8–11 years and 24 years, and the period of 3–4 years was influenced by human activities significantly; (3) prediction of annual sediment flux with the help of wavelet neural network (WNN) model is acceptable, which gives a better result than RBFN (Radial Basis Function Network) model.
Starting Page	1792
Ending Page	1795
File Size	528666
Page Count	4
File Format	PDF
ISBN	9781424459582
e-ISBN	9781424459612
DOI	10.1109/ICNC.2010.5584463
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-08-10
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	wavelet analysis Humans Artificial neural networks Predictive models Wavelet analysis Rivers Sediments neural network Wavelet coefficients Yellow River annual sediment flux
Content Type	Text
Resource Type	Article

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