Prediction Model of River Water Level Based on LS-SVM

Autor: Ding Haijiao, Che Wen-gang
Rok vydání: 2015
Předmět:
Zdroj: 2015 8th International Conference on Intelligent Computation Technology and Automation (ICICTA).
DOI: 10.1109/icicta.2015.164
Popis: In order to predict the changes of water level of natural river, this paper applied the method of LS-SVM, combining with sichuan zigong hydrologic measured water level data and flow data builded a double input single output (water level and flow-water level) river water level prediction model. Through the analysis of the prediction results, can draw the conclusion: The accuracy of the prediction model, which was established by LS-SVM is very high, can meet the needs of the river water level prediction.
Databáze: OpenAIRE