|Table of Contents|

Application of Phase Space Reconstruction and Neural Network in Flood Disaster Losing Forcasting(PDF)

《地球科学与环境学报》[ISSN:1672-6561/CN:61-1423/P]

Issue:
2006年第02期
Page:
89-92
Research Field:
Publishing date:

Info

Title:
Application of Phase Space Reconstruction and Neural Network in Flood Disaster Losing Forcasting
Author(s):
CAO Lian-hai CAO Bo CHEN Nan-xiang XU Jian-xin
Department of Geotechnical Engineering, North China College o f Water Conservancy and Hydroelectric Power, Zhengzhou 450008, Henan, China
Keywords:
phase space reconstruction neural network flood disaster losing forecasting model
PACS:
P426.6
DOI:
-
Abstract:
Introducing chaos theory in the disaster resources field, the forecasting models for the inundated area of flood disaster were brought forward integrating reconstruction of phase space and neural network. One-dimension inundated area series is developed to multi-dimension inundated area series with reconstruction of phase space, and the multi-dimension series include ergodic information, so that more abundant information can be found in fa- vor of ANN training. With neural network, non-linear problem can be solved better, as a result, forecasting can accord well with practice even more. The example indicates that the model has highly forecasting precision.

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Last Update: 2006-06-20