Neural network for travel demand forecast using GIS and remote sensing
Neural network for travel demand forecast using GIS and remote sensing
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DOI:
10.1109/ijcnn.2000.860810
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发表时间:
2000-07
期刊:
影响因子:
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通讯作者:
A. Dantas;Koshi Yamamoto;M. V. Lamar;Y. Yamashita
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文献类型:
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作者:
A. Dantas;Koshi Yamamoto;M. V. Lamar;Y. Yamashita
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 the model's basic formulation and the results of a case study conducted in the Boston metropolitan area.