Optimization Research And Its Performance Analysis On The Transfer Model Of Weighted Public Transport Networks

This article is based on the research of the weighted complex network model, combining theory with practice, and applies the theory to the actual transfer system so as to optimize transfer system and improve passengers travel efficiency.First, this paper puts forward a strength-driven weighted clique network evolution model which expands continuously by the addition of a new clique (maximal complete sub-graph) at each time step, and the cliques in the network overlap with each other. The model makes the network grow under the effect of mechanism of which the strength-driven weight continues to be strengthened. By studying the network properties of the model, we find both strength distribution and weights distribution have scale-free features, while the strength and the degrees have linear relationship. Based on the mean-field theory, the paper theoretically analyzes the model to prove that the strength distribution and the weights distribution are scale-free distributions. According to the results of the analysis, we can predict the dynamics of network growth and calculate the corresponding distribution and scale-free features. By comparison with other simulation results, the results based on mean-field theory and the statistical data of the model are highly consistent which indicates the validity of theoretical analysis of the model.Then, this paper has proposed a weight-driven weighted clique network evolution model. The network model is under the effect of weight-driven weighted mechanism, each time accompanied by a change of edge weights, and two new nodes are connected to the side of weight change at both ends which compose of a new clique added to the network, to promote the continued growth of network size. By studying the weights distribution, strength distribution and degree distribution, we find that they all have scale-free features, and strength and the degree have linear correlation. Based on the analysis of mean-field theory, we theoretically prove these distributions respectively. According to the comparison between theory proof and the simulation results we find that this network model is also a scale-free network model. Finally, the public transportation network data is abstracted as a weighted complex network model .We propose a time factor based on the average shortest path concept which is used to describe the size of the traffic between bus station. With breadth-first search algorithm for the bus transfer, we apply it to the Hangzhou bus transfer system, and ultimately get a best solution of transfer between stations based on average shortest path time factor. The actual bus data of Hangzhou and the introduction of Hangzhou Map are used in the system, so as to achieve the visualization of bus query results and bus transfer line. With an electronic map of the bus congestion map, people can effectively travel using the best travel program to choose the best bus lines.