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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/13929

Title: Learning Method Inspired on Swarm Intelligence for Fuzzy Cognitive Maps: Travel Behaviour Modelling
Authors: Leon, Maikel
Mkrtchyan, Lusine
Depaire, Benoit
Ruan, Da
Bello, Rafael
Vanhoof, Koen
Issue Date: 2012
Citation: Villa, Alessandro E.P.; Duch, Wlodzislaw; Erdi, Péter; Masulli, Francesco; Palm, Günther (Ed.). Artificial Neural Networks and Machine Learning - ICANN 2012 (22nd International Conference on Artificial Neural Networks; Proceedings, Part I), p. 718-725.
Series/Report: Lecture Notes in Computer Science
Series/Report no.: 7552
Abstract: Although the individuals' transport behavioural modelling is a complex task, it has a notable social and economic impact. Thus, in this paper Fuzzy Cognitive Maps are explored to represent the behaviour and operation of such systems. This technique allows modelling how the travelleers make decisions based on their knowledge of different transport modes properties at different levels of abstraction. We use learning of Fuzzy Cognitive Maps to describe travellers' behaviour and change trends in different abstraction levels. The results of this study will help transportation policy decision makers in better understanding of people's needs and consequently will help them actualizing different policy formulations and implementations.
URI: http://hdl.handle.net/1942/13929
ISBN: 978-3-642-33268-5
Category: C1
Type: Proceedings Paper
Validation: vabb, 2014
Appears in Collections: Research publications

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