Flood Forecasting Research Based on the Chaotic BP Neural Network Model

Chang Jun Zhu; Li Ping Wu; Sha Li

doi:10.4028/www.scientific.net/KEM.439-440.411

Paper Titles

Improve the Envelope of EMD with Piecewise Linear Fractal Interpolation
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A Service Robot with Lightweight Arms and a Trinocular Vision Sensor
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Improvement of a Structured Multi-Signature Scheme
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Application of Combined Matlab and VB Model in Water Pollution Control Planning
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Flood Forecasting Research Based on the Chaotic BP Neural Network Model
p.411

Wireless Transmission System Design of Main Shaft Hoist Load Data
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Community Intelligent Heat Meter and Remote Meter Reading System Design
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Logistics Center Location Selection Based on the Algorithm of Hybrid Particle Swarm Optimization
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The Intelligent Care System for Cardiac Patient
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Flood Forecasting Research Based on the Chaotic BP Neural Network Model

Abstract:

In view of the problem that the predictive results of flow quantity are not ideal for the predictive models at present. Based on the chaos identification to the flood system, chaos BP neural network model are developed combined chaos theory and BP neural netwok, flood sequences are disposed by phase-space reconstruction to be as training sample. Network structure can be determined by Matlab toolbox. The established chaos BP model is used to predict the phenomenon of peak value for Huayuankou hydrometric station in 2006. The results show that the predictive model combined chaos theory and BP neural network, has certain reference value to improve flood forecasting accuracy as a new attempt.