Application Research of Support Vector Machine Based on Particle Swarm Optimization in Runoff Forecasting
| Autor: | Fei Fei Sun, Li Xue Wang, Li Na Wang, Guo Feng Li, Ce Luan |
|---|---|
| Rok vydání: | 2012 |
| Předmět: |
Engineering
Mathematical optimization business.industry Generalization MathematicsofComputing_NUMERICALANALYSIS Particle swarm optimization Sample (statistics) General Medicine Term (time) Support vector machine ComputingMethodologies_PATTERNRECOGNITION Convergence (routing) Multi-swarm optimization business Surface runoff |
| Zdroj: | Applied Mechanics and Materials. :2303-2307 |
| ISSN: | 1662-7482 |
| DOI: | 10.4028/www.scientific.net/amm.226-228.2303 |
| Popis: | In view of the little sample, less data problems, mid-and-long term hydrologic forecasting is a case of which, Support Vector Machine (SVM) can solve this kind of problems perfectly. This paper introduced the basic optimization procedure and PSO-SVM modeling procedure. The PSO-SVM model has been applied in forecasting the monthly runoff of Dahuofang reservoir. The comparison between PSO-SVM and not-optimized SVM implied that the PSO-SVM has a fast convergence speed and strong generalization capability, also the related error has been decreased from 15.5% to 11.9%. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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