单变量核密度估计模型及其在径流随机模拟中的应用
Kernel Density Estimation Model and Its Application to Stochastic Generation in Hydrology and Water Resources
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摘要: 应用核密度估计理论构造了单变量多阶核密度估计模型。该模型是基于数据驱动的、不需对序列概串分布(正态分布、PⅢ型分布)和相依形式(线性或非线性)进行识别、适合于时间序列随机模拟的非参数模型。将单变量核密度估计模型用于中国金沙江流域屏山站日流量过程随机模拟,应用表明,该模型是适合于径流随机模拟的。Abstract: In this paper the kernel density estimation model based on kernel density estimation theories is established for time series of single variable.It belongs to a class of data-driven approach and avoids the form of probability distribution (normal or pⅢ)and the form of dependence (linear or nonlinear).The model has clear concept and singe structure.The model is applied to the stochastic generation of daily discharge time series at single station.The results indicate that the suggested model is suitable for stochastic simulation of hydrology time series.