长江科学院院报2018，Vol.35Issue(1)：36-39,46,5.DOI:10.11988/ckyyb.20160843
基于核密度估计的AM-MCMC算法在径流模拟中的应用
AM-MCMC Algorithm for Runoff Simulation Model Based on Kernel Density Estimation
摘要
Abstract
The simulation of runoff probability in an area in lack of runoff data is a difficulty in hydrological research.In this article,we try to establish the probability density function of monthly runoff flow by adopting kernal density estimation method,and give the solution by Markov Chain Monte Carlo (MCMC) simulation method based on Adaptive Metropolis (AM) algorithm.Case study shows that the AM-MCMC algorithm model based on kernel density estimation is of high accuracy and good application value.It can be used in areas in lack of data.关键词
径流模拟/概率分布/核密度估计/AM-MCMC算法/罗岙水库Key words
runoff simulation/probability distribution/kernel density estimation/AM-MCMC algorithm/Luo'ao Reservoir分类
建筑与水利引用本文复制引用
童坤,刘恒,耿雷华,徐澎波..基于核密度估计的AM-MCMC算法在径流模拟中的应用[J].长江科学院院报,2018,35(1):36-39,46,5.基金项目
南京水利科学研究院院基金项目(Y516011) （Y516011）
水利部公益性项目(201201020) （201201020）
