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Evaluating University Campus Traffic by Attribute Mathematical Recognition

机译:通过属性数学识别评估大学校园流量

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The high traffic volume in Chinese universities brings issues including accessibility and safety, which requires careful evaluation of campus-traffic with a quantitative and qualitative method. A multilevel index system based on attribute mathematical recognition is proposed. The upper-level includes five indexes, namely efficiency, accessibility, comfort, safety and traffic calming, which are further divided into the lower-level indexes. The indexes' weights are determined by variation coefficient method and the campus traffic level was identified by the confidence rules to avoid unreasonable estimation. A case study of Sun Yat-sen University East Campus is presented, whose travel environment was just passable in 2007 but greatly improved since 2009 after the road reconstruction and traffic regulations suggested by the authors. The evaluation accords with the opinion poll and the method is practical, rational and suitable for comparison.
机译:中国大学的高交通量带来了包括可访问性和安全性的问题,这需要仔细评估校园交通的定量和定性方法。提出了一种基于属性数学识别的多级索引系统。上层包括五个索引,即效率,可访问性,舒适性,安全性和交通平衡,其进一步分为较低级别的索引。索引的权重由变化系数法决定,校园流量通过置信度规则识别以避免不合理的估计。提出了对孙中山大学东校区的案例研究,其旅游环境刚刚在2007年通过,但自2009年自2009年之后大大提高,作者提出的道路重建和交通规则。评估符合民意调查和方法是实用的,理性的,适合比较。

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