论文部分内容阅读
随着城市轨道交通网络的不断扩大,换乘枢纽的地位越来越突出,成为影响轨道交通效率和服务水平的主要因素。分析了换乘枢纽的评价指标体系。由于指标信息数据的不完备性,利用模糊聚类对不完备信息表进行完备化,并引入经典粗糙集理论阐释了信息颗粒的含义,构造了信息颗粒;提出了基于粗糙信息颗粒的属性约简算法,建立了轨道交通换乘枢纽评价模型。通过示例说明了该方法的有效性,并给出了基于给定阈值的置信度评价规则集。
With the continuous expansion of urban rail transit network, the position of interchange hub becomes more and more prominent, becoming a major factor affecting the efficiency and service level of rail transit. The evaluation index system of transfer hub is analyzed. Due to the incompleteness of the index information data, fuzzy clustering is used to complete the incomplete information table, and the classical rough set theory is introduced to explain the meaning of the information particles, and the information particles are constructed. The attribute reduction based on the rough information particles Algorithm, established the evaluation model of rail transit hub. An example is given to illustrate the effectiveness of the proposed method and a set of confidence evaluation rules based on a given threshold.