Neural geo-spatial model for urban and transportation sustainability - system's diagnosis

A strategic planning model for vehicular air pollution analysis is presented. The model is based on the representation of the urban, transportation and environment conditions interacting under a neural geo-spatial approach to forecast vehicular air pollution for the stage of diagnosis, as a contribution for an urban and transportation sustainability. A case study in Nagoya City Area was conducted to verify the efficiency of the model and to evaluate the best NN structure and also changes in the hidden and output layers were simulated. The result reached expresses an efficient definition of the NN, and also allows the continuance of the research.