EVALUATION OF ARTIFICIAL NEURAL NETWORK APPLICATIONS IN TRANSPORTATION ENGINEERING
The increased interest in artificial neural networks (ANNs) seen in government and private research as well as business and industry has included relatively little activity in transportation engineering. The position that ANNs, as a branch of artificial intelligence, hold in the transportation engineering field is discussed, including the differences between ANNs and biological neural networks and expert systems, respectively. The characteristics of ANNs in different fields are discussed and summarized, and their potential applications in transportation engineering are explored. A case study of trip generation forecasting using one traditional method and two ANN models is presented to show the application potential of ANNs in transportation engineering. The results of each method are compared and analyzed, and it is concluded that the potential for using ANNs to enhance both software and hardware in transportation engineering applications is high, even in comparison with expert systems and other types of artificial intelligence technique.
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Availability:
- Find a library where document is available. Order URL: http://worldcat.org/isbn/0309052246
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Supplemental Notes:
- This paper appears in Transportation Research Record No. 1358, Vehicle Routing, Traveler ADIS, Network Modeling, and Advanced Control Systems. Distribution, posting, or copying of this PDF is strictly prohibited without written permission of the Transportation Research Board of the National Academy of Sciences. Unless otherwise indicated, all materials in this PDF are copyrighted by the National Academy of Sciences. Copyright © National Academy of Sciences. All rights reserved
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Authors:
- Faghri, Ardeshir
- Hua, Jiuyi
- Publication Date: 1992
Language
- English
Media Info
- Features: Figures; References; Tables;
- Pagination: p. 71-80
- Monograph Title: Vehicle routing, traveler ADIS, network modeling, and advanced control systems
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Serial:
- Transportation Research Record
- Issue Number: 1358
- Publisher: Transportation Research Board
- ISSN: 0361-1981
Subject/Index Terms
- TRT Terms: Artificial intelligence; Case studies; Forecasting; Neural networks; Software; Transportation engineering; Trip generation
- Uncontrolled Terms: Hardware
- Subject Areas: Administration and Management; Design; Highways; Operations and Traffic Management; Planning and Forecasting; Public Transportation; I10: Economics and Administration; I21: Planning of Transport Infrastructure; I72: Traffic and Transport Planning; I73: Traffic Control;
Filing Info
- Accession Number: 00626911
- Record Type: Publication
- ISBN: 0309052246
- Files: TRIS, TRB, ATRI
- Created Date: Feb 22 1993 12:00AM