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Modeling of Transport Demand
Analyzing, Calculating, and Forecasting Transport Demand

An essential guide for predicting and understanding demand for transportation services, including discussions of design, operation and maintenance

V.A Profillidis (Author), G.N. Botzoris (Author)

9780128115138, Elsevier Science

Paperback, published 29 October 2018

500 pages
22.9 x 15.1 x 3.1 cm, 0.77 kg

Modeling of Transport Demand explains the mechanisms of transport demand, from analysis to calculation and

forecasting. Packed with strategies for forecasting future demand for all transport modes, the book helps readers

assess the validity and accuracy of demand forecasts.

Forecasting and evaluating transport demand is an essential task of transport professionals and researchers

that affects the design, extension, operation, and maintenance of all transport infrastructures. Accurate demand

forecasts are necessary for companies and government entities when planning future fleet size, human resource

needs, revenues, expenses, and budgets. The operational and planning skills provided in Modeling of Transport

Demand help readers solve the problems they face on a daily basis.

Modeling of Transport Demand is written for researchers, professionals, undergraduate and graduate students

at every stage in their careers, from novice to expert. The book assists those tasked with constructing qualitative

models (based on executive judgment, Delphi, scenario writing, survey methods) or quantitative ones (based on

statistical, time series, econometric, gravity, artificial neural network, and fuzzy methods) in choosing the most

suitable solution for all types of transport applications.

1. Transport demand and factors affecting it2. Evolution and trends of transport demand3. Methods of modeling transport demand4. Executive judgment, Delphi, scenario writing and survey methods5. Statistical methods for transport demand modeling6. Trend projection and time series methods7. Econometric, gravity and the 4–step methods8. Artificial intelligence – Neural network methods9. Fuzzy methods

Subject Areas: Transport technology & trades [TR]

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