Neural Network for Travel Demand Forecast using GIS and Remote Sensing (2000)
AuthorsDantas, A., Yamamoto, K., Lamar, M.V., Yamashita, Y.show all
This paper describes an application of Neural Networks in the development of a travel forecast model for transportation planning. The model intends to quantify trips within the urban area through the representation of the land use-transportation system interaction. The data to express such a complex interaction is mainly obtained from Remote Sensing images that are processed in a Geographical Information System. We present, in this paper, model’s basic formulation and the results of a case study conducted in Boston metropolitan area.
CitationDantas, A., Yamamoto, K., Lamar, M.V., Yamashita, Y. (2000) Neural Network for Travel Demand Forecast using GIS and Remote Sensing. Como, Italy: IEEE-INNS-ENNS International Joint Conference on Neural Networks, 24-27 Jul 2000. Proceedings of the IEEE-INNS-ENNS, Vol. 4, 435-440.
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