Research on the Flood Forecasting Based on Coupled Machine Learning Model

KAN Guang-yuan , HONG Yang , LIANG Ke

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China Rural Water and Hydropower ›› 2018 ›› (10) : 165-169.

Research on the Flood Forecasting Based on Coupled Machine Learning Model

  • KAN Guang-yuan1,3 ,HONG Yang1 ,LIANG Ke2 
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Abstract

In recent years,machine learning models,such as artificial neural network ( ANN) ,have made great progresses in many fields, such as deep learning model for image recognition and reinforcement learning model for go software AlphaGo. In this paper,a coupled machine learning ( CML) model for flood forecasting is proposed. The CML model couples the ANN with the K nearest neighbour method by a specially designed modelling approach and is trained by multi-objective genetic and Levenberg-Marquardt algorithms. The model resolves the insufficient foreseeable period ( only one time -step ahead) ,not able to simultaneously optimize the ANN topology structure and parameter,the local minimum,and poor performance of single ANN problems concerning the traditional ANN model applications. Real-world application of the CML model in the Tunxi watershed flood forecasting indicates its satisfactory performance and reliability,which enlightens the possibility of further applications of the CML model in flood forecasting

Key words

coupled machine learning model / hydrological model / flood forecasting / artificial neural network / K nearest neighbor method

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KAN Guang-yuan , HONG Yang , LIANG Ke. Research on the Flood Forecasting Based on Coupled Machine Learning Model. China Rural Water and Hydropower. 2018, 0(10): 165-169

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