Transportation In The Analysis And Research Of The Optimal Allocation Of Resources

With the continuous growth of the city traffic. optimizing bus resources as possible as can is imperative. To improve the public transport capacity configuration, is not only able to help improve public transport operation efficiency, but also improve the bus service level, realize the balance of whole bus transport resource and create environment-friendly society.To solve the bus problems, only relying on increasing the number of public buses or adjusting the bus lines, can't resolve the problem ultimately, instead, increasing the number of public buses blindly, not only can cause public transport waste of resources, but also will increase the urban traffic pressure. Therefore, how to make full use of the existing public transport resources, and how to meet the interest of bus passengers and State Transit,under the premise of related resources to optimize the allocation, is the key to the problem.First of all, the factors that relevant factor of public transport capacity are comprehensively analysed so we characterize optimal allocation of public transport capacity as multi-objective optimization problem in this paper. Moreover. multi-objective optimization model is introduced that bases on game theory. By analysis of the original model, we introduce the Gini coefficient in the economic indicators. After quantization, the degree of resource allocation equilibrium is viewed as a new objective function by putting in the original model. A new and improved model is obtained finally. Applying to instance data. by adjustment, the share rate of the passenger volume (Gini coefficient) improved from0.29to0.21.we can conclude that the new model is better than the original model in line with reality from the balance of traffic distribution。This paper made clear that bus passenger forecast plays the key role in the entire capacity configuration flow. Accurate prediction of the passenger is the basis and premise of bus resources optimization allocation. In this paper.the bus passenger forecasting model based on the liman neural network is given. Finally.the forecast is carried on using the nearly eight years data of Beijing passengers. Finally by comparing with BP static neural network which is more popular currently, we discover that Elman neural network is of high precision than the BP neural network.