Please use this identifier to cite or link to this item:
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
Source: 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.
Document URI:
ISBN: 978-3-642-33268-5
Category: C1
Type: Proceedings Paper
Validations: vabb 2014
Appears in Collections:Research publications

Show full item record

Page view(s)

checked on May 16, 2022

Google ScholarTM



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.