二项-广义Pareto复合模型的极端海况要素推算
Extremesea condition element estimation of binomial-generalized Pareto compound model
邱玥 1庞亮 1董胜1
作者信息
- 1. 中国海洋大学工程学院,山东青岛 266100
- 折叠
摘要
在复合极值分布理论的基础上,构造基于短期观测样本的二项-广义Pareto复合极值分布模型,并应用于极端海况要素推算.结果表明:二项-广义Pareto复合极值分布模型具有良好的拟合效果,能够合理反映极端海况的长期概率分布特征,弥补了传统方法需要长期原始海况数据的缺陷,且模拟结果与采用长期数据资料,利用Gumbel模型、对数正态模型得到的结果相差不大,在预测波高方面有很强的适用性.
Abstract
Based on the compound extreme value distribution theory,binomial-generalized Pareto com-pound extreme value distribution model based on short-term observation samples was constructed and applied to the prediction of extreme sea condition elements.The results showed that the binomial-gen-eralized Pareto compound extreme value distribution model had good fitting effect,could reasonably re-flect the long-term probability distribution characteristics of extreme sea conditions and made up for the defect of traditional methods need long-term raw sea condition data.The simulation results were simi-lar with the results using long-time data,the Gumbel model and the lognormal model,and had strong applicability in the prediction of wave height.
关键词
复合极值分布/极端海况/短期资料/概率预测/设计波浪Key words
compound extreme value distribution/extreme sea condition/short-term data/probabilistic prediction/design wave引用本文复制引用
出版年
2024
NETL
NSTL
万方数据