城市交通组织优化仿真模型的参数估计新方法

从逼近性较好和易于计算机实现两个角度,对城市交通组织优化仿真模型中参数估计方法进行了研究,给出了极大似然估计法、范数理论的数据拟合以及三次B样条拟合方法,并对3种方法的特点和适用条件进行了比较。极大似然估计法基于数理统计理论,建立在已有试验数据基础上,适合于精度要求不高的情况;范数理论的数据拟合采用欧氏范数(1-范数,2-范数,无穷范数)作为误差量度的准则,理论严密,有明确的几何意义,适合于拟合函数曲线特征比较明显的情况;数据分布规律不明显时,采用三次B样条函数拟合。实例表明,3种仿真模型参数估计方法均是可行的,平均绝对误差从小到大依次为三次B样条拟合方法、2-范数拟合方法和极大似然估计法,分别为0.002 80、.016 90、.017 1。在实际工程中,应分别采用3种方法进行估计,选择误差较小的方法。

Parameter estimation new algorithms in static simulation models for urban traffic organization and optimization

From two aspects of better approximation and easier programming,this paper studied the parameter estimation algorithms for simulation models in urban traffic organization and optimization.It presented the maximum-likelihood method,normal number and B-splines approximation and also made a comparison of their characteristics and using conditions.The maximum-likelihood method,based on the mathematical statistics and experimental data,is fit for the condition of lower accuracy.The normal number approximation uses Euclidean norm(1-norm,2-norm and infinitesimal norm) as its error measure,it has clear geometrical meaning,it is suitable for the condition when the rule of data curve is clear.When the data distribution rule is obscure,B-splines approximation is useful.An example shows that these three methods are feasible,the average absolute error can be ordered as B-splines approximation,normal number approximation and maximum-likelihood method by descending sort,and their average absolute errors are 0.002 8,0.016 9,0.017 1 individually.In the actual engineering,these three methods should be used separately to choose the one with smaller error.3 tabs,1 fig,12 refs.