Research of Flood Prediction Based on Subjective/Objective Evidences Fusion Model

Wei Wu; Yan Ming Chen

doi:10.4028/www.scientific.net/AMR.532-533.1272

Paper Titles

A New Method for Noisy Speech Classification Based on Gaussian Mixture Models
p.1253

Multi-Objects Detection in Remote Sensing Images Using Multiple Kernel Learning
p.1258

Research on Construction of Semantic Web of 3D Model Database
p.1263

Key Technologies in the Construction of a GIS System for Weather Data
p.1268

Research of Flood Prediction Based on Subjective/Objective Evidences Fusion Model
p.1272

A Multi-Dimensional Time Series Data Mining Model for Weather Forecast
p.1277

Research and Improvement on Content-Based Web Search Engine
p.1282

Simulation and Spectral Analysis of Sea Wave
p.1287

Computer Simulations of Chua’s Circuits with Small-World Connection
p.1292

HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 532-533Research of Flood Prediction Based on...

Research of Flood Prediction Based on Subjective/Objective Evidences Fusion Model

Abstract:

This paper presents a model by combining BP neural network and DS evidential reasoning, which not only achieves the feature level fusion of all subjective and objective evidences in various domains and layers, but also makes distinct models complement each other. By the experiment, this method improves classification precision by 7.9 percent and reduces the time complexity of algorithm. The model solves the problems such as high complexity of algorithms and low accuracy rate of classifications lie in the flood prediction using single models.

You might also be interested in these eBooks

View Preview

Info:

Periodical:

Advanced Materials Research (Volumes 532-533)

Pages:

1272-1276

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.532-533.1272

Citation:

Cite this paper

Online since:

June 2012

Authors:

Wei Wu, Yan Ming Chen

Keywords:

BP Neural Network (BPNN), DS Evidence Theory, Flood Prediction, Objective Evidences Fusion, Subjective Evidences Fusion

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

References

[1] LINAS J, WAL TZ E. Multi2sensor data fusion[M]. Norwood, Massachusetts: Artech House , 1991. 27-56.

Google Scholar

[2] Pei Lin Lan，Qiang Ji，Carl G．Information fusion with Bayesian networks for Monitoring human fatigue[A]. Proceedings of the 5th International Conference on Information Fusion[C]. Annapolis，USA: ISIF，2002，535-542.

DOI: 10.1109/icif.2002.1021200

Google Scholar

[3] He You，Wang Guo Hong．Multi-sensor information fusion and application [M]．BeiJing: Publishing House of Electronics Industry，2000. 24－35.

Google Scholar

[4] Xu L Y , Du X D , Zhao H. A pplication of neural f usion to accident forecast in hydropower station[ A ]. Proceedings of the Second International Conference on Information Fusion[C]. Los Angeles : Omni Press , 1999. 1166 - 1171.

Google Scholar

[5] Hall D. Mathematical Techniques in Multisensor Data Fusion [M]. Norwood: Artech House, 1992. 235–238.

Google Scholar