Ideal N-depth Clique Network Model and Application Research on the Bus Transport Network
|School||Zhejiang University of Technology|
|Course||Control Theory and Control Engineering|
|Keywords||complex network the ideal n-depth clique network model bus transport network model transport network optimization network performance|
Generally, we call large network which include one or several features in self-organization, self-similarity, small world and scale-free the complex network. Bus transport network is a complex network. Researching on complex network theory and its applications has become a new prospective direction since the last decade. This paper uses complex network theory to research bus transport network, proposes an ideal n-depth clique network model and studies its application on bus transport network. The main work and achievements are as follows:1. For improving the entire service performance of the bus transport network, we propose a bus transport network model with ideal n-depth clique topology. It has similar network properties with the real bus transport network. On the other hand, comparing with BTN, it has a higher the clustering extent of bus routes, smaller network diameter and lower average shortest path time factor. Therefore, it has higher transfer efficiency which helps improve the service quality of bus systems.2. In order to improve the transfer performance and to reduce the average transfer times as optimization objective, we propose a bus transport network optimization method based on ideal n-depth clique network. The entire service quality has improved after using this optimizing method on the bus transport network in Hangzhou. Meanwhile, a transfer algorithm applying on bus transport networks with ideal n-depth clique network has been proposed.3. Studies on the network performance of bus transport networks with ideal n-depth clique network topology have been done from network robustness and spread behavior views respectively. Through comparing the new network model with real bus transport network and BTN model, we research the network robustness on random failure and deliberate attack respectively. Also studies on the bus network congestion propagation behavior have been done under the SIS model.4. An ArcGIS-based bus transport network optimization system has been realized to present the application of the bus transport network optimization method on the transport network in Hangzhou. The system use this method to give out specific adjustments combine with information on city roads, then display the bus lines and sites before and after optimization on the map. The final system also implements the transfer algorithm based on the ideal n-depth clique network.5. Finally, we summarize this paper and give out some prospects of the further research.