A New Approach for Hierarchical Dividing to Passenger Nodes in Passenger Dedicated Line
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초록
China possesses a passenger dedicated line system of large scale, passenger flow intensity with unevendistribution, and passenger nodes with complicated relations. Consequently, the significance of passengernodes shall be considered and the dissimilarity of passenger nodes shall be analyzed in compiling passengertrain operation and conducting transportation allocation. For this purpose, the passenger nodes need to behierarchically divided. Targeting at problems such as hierarchical dividing process vulnerable to subjectivefactors and local optimum in the current research, we propose a clustering approach based on self-organizingmap (SOM) and k-means, and then, harnessing the new approach, hierarchical dividing of passengerdedicated line passenger nodes is effectuated. Specifically, objective passenger nodes parameters are selectedand SOM is used to give a preliminary passenger nodes clustering firstly; secondly, Davies–Bouldin index isused to determine the number of clusters of the passenger nodes; and thirdly, k-means is used to conductaccurate clustering, thus getting the hierarchical dividing of passenger nodes. Through example analysis, thefeasibility and rationality of the algorithm was proved.
Abstract
China possesses a passenger dedicated line system of large scale, passenger flow intensity with unevendistribution, and passenger nodes with complicated relations. Consequently, the significance of passengernodes shall be considered and the dissimilarity of passenger nodes shall be analyzed in compiling passengertrain operation and conducting transportation allocation. For this purpose, the passenger nodes need to behierarchically divided. Targeting at problems such as hierarchical dividing process vulnerable to subjectivefactors and local optimum in the current research, we propose a clustering approach based on self-organizingmap (SOM) and k-means, and then, harnessing the new approach, hierarchical dividing of passengerdedicated line passenger nodes is effectuated. Specifically, objective passenger nodes parameters are selectedand SOM is used to give a preliminary passenger nodes clustering firstly; secondly, Davies–Bouldin index isused to determine the number of clusters of the passenger nodes; and thirdly, k-means is used to conductaccurate clustering, thus getting the hierarchical dividing of passenger nodes. Through example analysis, thefeasibility and rationality of the algorithm was proved.
참고문헌 (21)
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