2013
DOI: 10.1080/18756891.2013.816025
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Tackling Travel Behaviour: An approach based on Fuzzy Cognitive Maps

Abstract: Although the individuals" transport behavioural modelling is a complex task, it can produce a notable social and economic impact. In this paper, Fuzzy Cognitive Maps are explored to represent the behaviour and operation of such complex systems. An automatic approach to extract mental representations from individuals and convert them into computational structures is defined. For the creation of knowledge bases the use of Knowledge Engineering is accounted and later on the data is transferred into structures bas… Show more

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Cited by 16 publications
(5 citation statements)
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“…-If λ > 0 is large enough there can be multiple solutions, where many of these fixed points may be linearly stable. For better understanding of the above affirmation let us consider a FCM concerning travel behavior analysis [24]. This model involves three kinds of variables which are denoted as map concepts, and three further nodes for each transport alternative (bus, bike or car).…”
Section: Stability On Non-discrete Fuzzy Cognitive Mapsmentioning
confidence: 99%
“…-If λ > 0 is large enough there can be multiple solutions, where many of these fixed points may be linearly stable. For better understanding of the above affirmation let us consider a FCM concerning travel behavior analysis [24]. This model involves three kinds of variables which are denoted as map concepts, and three further nodes for each transport alternative (bus, bike or car).…”
Section: Stability On Non-discrete Fuzzy Cognitive Mapsmentioning
confidence: 99%
“…Therefore the FCM theory seems to be an appropriate choice. Recently, M. León et al [25,26] proposed a novel modeling based on Cognitive Mapping theory to characterize mental representations of transportation experts.…”
Section: Second Case Study: Travel Behavior Analysis Using Fcm Theorymentioning
confidence: 99%
“…From the machine learning point of view, the proposed topology leads to a complex multi-objective regression problem, where the expected utility that reports the selection of a specific transport mode should be estimated. However, as a result from [26], we know that some concepts are severely susceptible to expert's criteria and they are often superfluous or contradictory. Then, finding central nodes could reduce the map complexity, allowing the knowledge extraction tasks.…”
Section: Proposed Fcm Topologymentioning
confidence: 99%
“…FCMs have received increasing attention among researchers and both practical and theoretical results have been introduced. Some representative application fields include: decision making [5], system control [6], engineering [7], protein modeling [8], transport management [9], intrusion detection [10], etc. Also, Papakostas et al [11] introduced FCM-based classifiers as light grey box models, being used for classification tasks.…”
Section: Introductionmentioning
confidence: 99%