检索规则说明:AND代表“并且”;OR代表“或者”;NOT代表“不包含”;(注意必须大写,运算符两边需空一格)
检 索 范 例 :范例一: (K=图书馆学 OR K=情报学) AND A=范并思 范例二:J=计算机应用与软件 AND (U=C++ OR U=Basic) NOT M=Visual
机构地区:[1]东南大学交通学院,南京210096 [2]山东理工大学交通与车辆工程学院,淄博255049
出 处:《武汉理工大学学报(交通科学与工程版)》2009年第5期1008-1011,共4页Journal of Wuhan University of Technology(Transportation Science & Engineering)
基 金:国家高技术研究发展计划项目资助(批准号:2008AA11Z201)
摘 要:针对二元logit模型在出行生成预测应用时忽略了变量差异性的缺点,提出了其可观测变量参数β'服从对数正态分布的假设,根据美国PUMS居民出行调查的前300个相关数据,通过参数标定对该假设的合理性进行了验证.采用SAS仿真系统对参数进行标定的结果表明:当部分参数服从对数正态分布时,所有参数的t检验值均在[-1,1]区间之外,从而验证了假设的合理性.分别利用改进前的模型与改进后的模型进行城市居民出行生成预测,结果显示后者的预测精度明显高于前者,进一步验证了应用改进后的二元logit模型进行居民出行生成预测有显著效果.To overcome the disadvantage of the binary logit model used in existing resident trip models that neglects the difference of known variables, this paper developed a hypothesis that random parameters β' obeyed log normal distribution. It was validated by demarcating the parameters, which was based on 300 data of PUSM in USA. These parameters were estimated using SAS software. Its result shows that all the parameters' T values are out of [-1,1] interval when assuming that some parameters obey log normal distribution and proves the rationality of the assumption. The resident trip model was forecasted adopting the previous and improved models. The result further shows that the forecasting precision of the latter model is much higher than the former one's, which reveals that the improved binary logit model has effective application.
关 键 词:二元logit 对数正态分布 SAS 参数标定 模型验证
分 类 号:U491.112[交通运输工程—交通运输规划与管理]
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在链接到云南高校图书馆文献保障联盟下载...
云南高校图书馆联盟文献共享服务平台 版权所有©
您的IP:216.73.216.229