scholarly journals The Change of Bus Network Service System in the Central Area of Kanagawa Prefecture

1986 ◽  
Vol 38 (4) ◽  
pp. 360-376
Author(s):  
Koichi USHIKUBO

2011 ◽  
Vol 11 (7) ◽  
pp. 60-69
Author(s):  
Dong-Yun Lee ◽  
Yoon-Ae Ahn ◽  
Jin-Young Jung ◽  
Jun-Hwan Lee ◽  
Han-Jin Cho




2014 ◽  
Vol 571-572 ◽  
pp. 567-571
Author(s):  
Dao Sheng Mu ◽  
Hao Ming Wang

With the rapid spread of network communication technology, the demand of reliability of the network service system is higher and higher for various industries. Any service failure will bring huge loss to the enterprise or individuals. So HA cluster system is increasingly favored by people as an important means of disaster. In this context, this paper analyzed the characteristics and role of HA cluster and the existing HA cluster software. Finally, in terms of optimization of the cluster mode scheme, disk filter way and the monitoring mode program, the corresponding software design scheme selection was put forward.





2019 ◽  
Vol 8 (11) ◽  
pp. 486 ◽  
Author(s):  
Xiping Yang ◽  
Shiwei Lu ◽  
Weifeng Zhao ◽  
Zhiyuan Zhao

The urban bus service system is one of the most important components of a public transport system. Thus, exploring the spatial configuration of the urban bus service system promotes an understanding of the quality of bus services. Such an understanding is of great importance to urban transport planning and policy making. In this study, we investigated the spatial characteristics of an urban bus service system by using the complex network approach. First, a three-step workflow was developed to collect a bus operating dataset from a public website. Then, we utilized the P-space method to represent the bus service network by connecting all bus stop pairs along each bus line. With the constructed bus network, a set of network analysis indicators were calculated to quantify the role of nodes in the network. A case study of Shenzhen, China was implemented to understand the statistical properties and spatial characteristics of the urban bus network configuration. The empirical findings can provide insights into the statistical laws and distinct convenient areas in a bus service network, and consequently aid in optimizing the allocation of bus stops and routes.







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