上海交通大学学报

上海交通大学学报（自然版）

• 天文学、地球科学 • 上一篇    下一篇

最大熵分布在波高长期统计中的应用

程竞姣,朱志夏   

  1. (上海交通大学 船舶海洋与建筑工程学院， 上海 200030)
  • 收稿日期:2009-09-11 修回日期:1900-01-01 出版日期:2010-06-30 发布日期:2010-06-30

Application of Maximum Entropy Distribution in Longterm Wave Height Statistics

CHENG Jingjiao,ZHU Zhixia   

  1. (School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiaotong University, Shanghai 200030, China)
  • Received:2009-09-11 Revised:1900-01-01 Online:2010-06-30 Published:2010-06-30

摘要： 基于最大熵原理，推导出最大熵分布概率密度函数，同时介绍了目前在有效波高长期统计分布中运用较多的参数化模式，并将这2种方法应用于有效波高的长期统计分布中.为了检验2种方法的准确性，选用我国东海海域浮筒长期实测风、波浪数据，进行有效波高的概率密度函数拟合，将计算结果与实测数据绘成直方图并进行了比较.结果表明，最大熵分布概率密度函数中的参量γ值能够表征实际海况的复杂程度，且其在不同风速下与实测数据均吻合良好；而由参数化模式推导出的有效波高概率密度函数，在风速较小时与实测数据的吻合程度比风速较大时好，在风速较大时会出现偏离.

关键词: 有效波高, 最大熵分布, 参数化模式, 概率密度函数

Abstract: The maximum entropy probability density function (PDF) was derived based on the maximum entropy principle. In addition, the widely used parameterized model in longterm significant wave height distribution was introduced. The two methods were applied to describe the longterm significant wave height distribution. In order to test the accuracy of these two methods, the longterm winds and waves data measured by buoys in the East China Sea were selected to fit the significant wave height distribution. Moreover, PDFs of the abovementioned two methods were compared with the observed data. The result shows that the value of parameter γ in PDF of the maximum entropy distribution can demonstrate the complexity of the sea states, besides, PDF of the maximum entropy distribution fits well at different wind speed. Whereas the PDF derived from the parameterized model fits better with the observed data at lower wind speed than at higher wind speed; the derivation occurs in the latter case.