Learning method inspired on swarm intelligence for fuzzy cognitive maps: Travel behaviour modelling

Maikel León, Lusine Mkrtchyan, Benoît Depaire, Da Ruan, Rafael Bello, Koen Vanhoof

    Research outputpeer-review


    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 travellers 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.

    Original languageEnglish
    Title of host publicationArtificial Neural Networks and Machine Learning, ICANN 2012 - 22nd International Conference on Artificial Neural Networks, Proceedings
    Number of pages8
    EditionPART 1
    StatePublished - 2012
    Event22nd International Conference on Artificial Neural Networks, ICANN 2012 - Lausanne
    Duration: 11 Sep 201214 Sep 2012

    Publication series

    NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    NumberPART 1
    Volume7552 LNCS
    ISSN (Print)0302-9743
    ISSN (Electronic)1611-3349


    Conference22nd International Conference on Artificial Neural Networks, ICANN 2012

    ASJC Scopus subject areas

    • Theoretical Computer Science
    • General Computer Science

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