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Flood risk assessment model based on particle swarm optimization rule mining algorithm.
- Source :
-
Xitong Gongcheng Lilun yu Shijian (Systems Engineering Theory & Practice) . Jun2013, Vol. 33 Issue 6, p1615-1621. 7p. - Publication Year :
- 2013
-
Abstract
- Particle swarm optimization (PSO) as a novel intelligent optimization algorithm has been used successfully in many fields, but its application to flood hazard risk assessment is a new research topic. This paper introduces the theory and flow of application of particle swarm optimization rule mining (PSO-Miner) algorithm to flood damage risk assessment. This paper selected Beijiang River Basin, China, as study area for flood damage risk assessment based on PSO-Miner algorithm and BPANN method. The results of a case study indicate that the advantages of PSO-Miner algorithm can be summarized as follows: It does not assume an implicit assumption for processing dataset and has strong robustness; it can mine very simple assessment rules; it can have a better performance than BPANN model. So the PSO-Miner algorithm provides a new approach for flood risk assessment. [ABSTRACT FROM AUTHOR]
Details
- Language :
- Chinese
- ISSN :
- 10006788
- Volume :
- 33
- Issue :
- 6
- Database :
- Academic Search Index
- Journal :
- Xitong Gongcheng Lilun yu Shijian (Systems Engineering Theory & Practice)
- Publication Type :
- Academic Journal
- Accession number :
- 90456375