Neural network for travel demand forecast using GIS and remote sensing

Author

Dantas, André ; Yamamoto, Koshi ; Lamar, Marcus V. ; Yamashita, Yaeko

Author_Institution

Dept. of Civil Eng., Nagoya Inst. of Technol., Japan

Volume

4

fYear

2000

fDate

2000

Firstpage

435

Abstract

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

Keywords

feedforward neural nets; geographic information systems; multilayer perceptrons; town and country planning; transportation; Boston metropolitan area; GIS; geographical information system; land use-transportation system interaction; remote sensing images; transportation planning; travel demand forecast; urban area; Civil engineering; Demand forecasting; Economic forecasting; Geographic Information Systems; Information systems; Neural networks; Predictive models; Remote sensing; Transportation; Urban areas;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks, 2000. IJCNN 2000, Proceedings of the IEEE-INNS-ENNS International Joint Conference on

Conference_Location

Como

ISSN

1098-7576

Print_ISBN

0-7695-0619-4

Type

conf

DOI

10.1109/IJCNN.2000.860810

Filename

860810