基于最大信息熵原理的居民出行分布模型  

Inhabits trip distribution model based on maximum information entropy theory

作　　者：曲昭伟[1] 姚荣涵[1] 王殿海[1] 

机构地区：[1]吉林大学交通学院,吉林长春130025

出　　处：《吉林大学学报（工学版）》2003年第2期15-19,共5页Journal of Jilin University:Engineering and Technology Edition

基　　金：国家自然科学基金资助项目(70071039);吉林省杰出青年基金资助项目(20010114);高等学校骨干教师资助计划项目(1000)。

摘　　要：为寻求居民出行分布的普适性模型,引入最大信息熵原理,据此建立了居民出行分布的熵模型。并通过改变约束条件推导出了居民出行分布中常见的几种模型。鉴于最大信息熵模型中参数标定比较困难,提出了确定系统分布的熵方法。实验验证表明这种方法简单可行,是对最大信息熵原理的扩充。本文的研究成果可以用于居民出行分布及其相关问题的研究。In order to find general models,several entropy models are put forward according to the maximum information entropy theory in inhabits trip distribution.By changing limited condition,several common models are proved.Because of the difficulty in calibrating parameters in the maximum information entropy models,the entropy method that can effectively select models is used to describe the system distribution.The survey data supports that this method is simple and feasible.And this method is the expansion of the maximum information entropy theory.The models can be applied to the study on the problems of inhabits trip distribution.

关 键 词：出行分布 最大信息熵原理 分布函数 

分 类 号：U491.12[交通运输工程—交通运输规划与管理]