Evaluating the Ecological Sustainable Transportation System with An Application of Radial Basis Function Neural Network

Abstract

Abstract The ecological and sustainable development of urban transportation system is critical to improving the overall quality of life and achieving the goals of climate protection and sustainable development. The study focused on factors from level of social and economic development, the quality of transport service and urban ecological environment to develop a comprehensive assessment indicator system. A novel method for evaluating the ecological sustainable transportation system based on the radial basis function neural network(RBFNN)was proposed. Results of comparative experiments between RBFNN and the conventional BP neural network (BPNN) showed that the accuracy of RBFNN was 8.3% higher than that of BPNN while the training time was 27.2s lesser and the Root Mean Square Error (RMSE) was 0.15 smaller. In the case of Shenzhen, China, the proposed model gave a reasonable evaluation, which implied that RBFNN brought forward a new perspective for further research.