Neural Networks in Transport Applications
Published on 28. September 1998
Book
Hardback
388 pages
978-1-84014-808-4 (ISBN)
Description
The analysis of human behaviour from the viewpoint of network developments has gained much scientific attention. Especially in a spatial context, many network models have been designed. Network models centre their analysis around the spatial behaviour of individuals or groups in an organized pattern of nodes and links. Since the 1970s, a wide range of such models has been developed and applied. Examples are linear programming models, chaos models, spatial competition models and many others. Some of these models were rooted in behavioural foundations of social or economic choice, others were based on analogous interpretations from the natural sciences. Some of these models are based on macro minimizing principles. There is thus a great variety of approaches to the analysis of network behaviour. This volume aims to offer an overview of the potential of neural network analysis for research applications in the transportation sector. It does not only focus on engineering types of approaches, but also on social science applications in the transport systems examined at VTT in Finland.
More details
Language
English
Place of publication
United Kingdom
Publishing group
Taylor & Francis Ltd
Target group
College/higher education
Professional and scholarly
Illustrations
figures, tables
Dimensions
Height: 159 mm
Width: 225 mm
ISBN-13
978-1-84014-808-4 (9781840148084)
Copyright in bibliographic data is held by Nielsen Book Services Limited or its licensors: all rights reserved.
Schweitzer Classification
Persons
Content
Theoretical considerations: neural networks - an overview and applications in the space economy, travel behaviour, performance of backpropogation ANN with different training parameters for modelling, daily travelling viewed by self-organizing maps, neural networks and logit models applied to commuters' mobility in the metropolitan area of Milan, neural networks as adaptive logit models, neural network analysis of travel behaviour, a methodology for modelling driver behaviour in signalized urban intersections using artificial neural networks. Traffic flow: traffic light signal junction control by neural networks; exploring traffic systems by elasticity analysis of neural networks; factors influencing the performance of a neural network driver decision model - a case study using simulated data; neural network models applied to tarrif flow problems; two dimensional estimation of speed flow-relationships with backpropogation neural networks. Traffic management: the application of fuzzy multiobjective and artificial neural networks for urban public transit equilibrium; the impact of data quantity on the performance of the neural networks freeway incident detection models; predicting parking characteristics - the use of neural networks to support parking management; travel time prediction for freeway traffic information by neural network driven fuzzy reasoning.