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[1]GUO Hao,XING Zhen-xiang,FU Qiang,et al.RBF Neural Network of K-Means Algorithm Based on Density Parameter and the Application to the Rainfall Forecasting[J].Research of Soil and Water Conservation,2014,21(06):299-303.

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RBF Neural Network of K-Means Algorithm Based on Density Parameter and the Application to the Rainfall Forecasting

Research of Soil and Water Conservation[ISSN 1005-3409/CN 61-1272/P] Volume: 21 Number of periods: 2014 06 Page number: 299-303 Column: Public date: 2014-12-28

Title:: RBF Neural Network of K-Means Algorithm Based on Density Parameter and the Application to the Rainfall Forecasting

Author(s):: GUO Hao¹, XING Zhen-xiang^1,2,3, FU Qiang^1,2,3, LI Jing¹; 1. College of Water Conservancy & Civil Engineering, Northeast Agricultural University, Harbin 150030, China;
2. Collaborative Innovation Center of Grain Production Capacity Improvement in Heilongjiang Province, Harbin 150030, China;
3. Key Lab of Water-Saving Agriculture of Heilongjiang University, Harbin 150030, China

Keywords:: hydrology; rainfall forecasting; radial basis function neural network; density parameter; K-means

CLC:: P338

DOI:: -

Abstract:: The radial basis function (RBF) neural network is a feed-forward artificial neural network with high convergence speed and strong approximation capability. In order to improve the training rate of the RBF, a K-means algorithm based on density parameter was introduced to determine clustering center, which could reduce the sensitivity of traditional K-means algorithm for initial clustering centers. A rainfall forecasting model of RBF based on K-means algorithm was built, which was applied to forecasting monthly rainfall over the Youyi Farm in Naolihe catchment during the flood season, aiming to test the effectiveness of this model. The case study showed that the mean relative error of rainfall forecasting in flood season (from June to September) of the year 2008, 2009 and 2010 was 9.270 7%, and the deterministic coefficient was 0.96. It demonstrated a higher forecasting accuracy compared to a RBF model based on a standard K-means algorithm and BP (Back Propagation) model, and the rainfall forecasting results met the requirements of hydrologic prediction.

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