Application of K-Means Cluster and Rough Set in Classified Real-Time Flood Forecasting

Abstract:

A new classified real-time flood forecasting framework was presented. Firstly, the historical floods were classified by K-means cluster, according to the hydrological factors. Then rough set was used to extract operation rules for flood forecasting. Following, the conceptual hydrological model was constructed and Genetic Algorithm (GA) was used to calibrate the hydrological model parameters. In simulation, River A is taken as study example. The categories of parameters are selected in operation according to flood information and rules. The result is compared with traditional flood forecasting. It demonstrates the performance of classified framework is improved in terms of accuracy and reliability.

• Periodical: Advanced Materials Research (Volumes 1092-1093)
• Pages: 734-741
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.1092-1093.734
• Online since: March 2015
• Authors: Heng Qing Wu*, Qiang Huang, Wei Xu, Shu Feng Xi
• Keywords: Conceptual Hydrological Model, Flood Forecasting, K-Means Cluster, Real-Time, Rough Set

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