Fuzzy Cognitive Maps: a model for intelligent supervisory control systems

Stylios, Chrysostomos; Groumpos, Peter P.

doi:10.1016/s0166-3615(98)00139-0

Cited by 147 publications

(98 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Thus, FCMs allow for a relatively simple knowledge aggregation, obtained from several experts. The aggregation of FCMs aims at improving the reliability of the final model which is less susceptible to potentially erroneous beliefs of a single expert [112]. It is common that experts evaluate different set of concepts.…”

Section: Aggregating Procedures For Fuzzy Cognitive Mapsmentioning

confidence: 99%

Tackling Travel Behaviour: An approach based on Fuzzy Cognitive Maps

León¹,

Nápoles²,

Bello³

et al. 2013

IJCIS

View full text Add to dashboard Cite

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 based on Fuzzy Cognitive Maps. Once the maps are created, their performances get improved through the use of a Particle Swarm Optimisation algorithm as a learning method, readjusting its predicting capacity from stored scenarios, where individuals left their preferences in front of random situations. Another important result is clustering the maps for knowledge discovery. This permits to find useful groups of individuals that policymakers can use for simulating new rules and policies. After related maps are identified, to merge them as a unique structure could benefit for different usages. Therefore an aggregating procedure is elaborated for this task, constituting an alternative approach for selecting a centroid of a specific estimated group, and therefore having, in only one structure, the knowledge and behavioural acting from a collection of individuals. Learning, clustering and aggregation of Fuzzy Cognitive Maps are combined in a cascade experiment, with the intention of describing travellers" behaviour and change trends in different abstraction levels. The results of this approach will help transportation policy decision makers to understand the people"s needs in a better way, consequently will help them actualising different policy formulations and implementations.

show abstract

Section: Aggregating Procedures For Fuzzy Cognitive Mapsmentioning

confidence: 99%

Tackling Travel Behaviour: An approach based on Fuzzy Cognitive Maps

León¹,

Nápoles²,

Bello³

et al. 2013

IJCIS

View full text Add to dashboard Cite

show abstract

“…The interrelationships among these concepts -main characteristics of the system -are depicted as fuzzy weighted arcs between concepts [7]. Experts use IF-THEN rules in order to describe the relationship among concepts, and then all these rules are combined and Fuzzy Cognitive Map is developed [8].…”

Section: Fuzzy Cognitive Mapsmentioning

confidence: 99%

The challenge of using soft computing for decision support during labour

Stylios¹,

Georgoulas²,

Groumpos³

2001

PsycEXTRA Dataset

View full text Add to dashboard Cite

Abstract-This paper presents the development of a Decision Support System for managing the labour based on the Soft Computing technique of Fuzzy Cognitive Maps. During labour, obstetricians manage and take decisions on the fetus delivery and the procedure of the labour, monitoring continuously a visual recording of the fetus heart signal and uterine contractions and they also take under consideration other physiological medical measurements and factors. Obstetricians utilize their experience and they decide either to proceed to a natural labour or to a Caesarean section. The developing system for managing labour delivery will combine evaluation of cardiotocographic signal with other physiological data in order to create an advanced Decision Support System.

show abstract

“…Over the last 10 years, a variety of FCMs have been used for representing knowledge and artificial intelligence in engineering applications, for instance, fault detection [1], geographical information systems [2] and modelling the supervision of distributed systems [3]. FCMs have been also used for several tasks like web data mining [4], and medical decision-making [5].…”

Section: Introductionmentioning

confidence: 99%

A Weight Adaptation Method for Fuzzy Cognitive Maps to a Process Control Problem

Papageorgiou

Groumpos

2004

Computational Science - ICCS 2004

View full text Add to dashboard Cite

Abstract. Fuzzy Cognitive Maps constitute an attractive modeling approach that encompasses advantageous features. The most pronounces are the flexibility in system design, model and control, the comprehensive operation and the abstractive representation of complex systems. The main deficiencies of FCMs are the critical dependence on the expert's opinion and the potential convergence to undesired steady states. In order to overcome these deficiencies a possible solution is the utilization of learning methods to adapt the causeeffect relationships of the FCM model. This research work examines the formulation of a weight adaptation method suitable for FCMs based on nonlinear Hebbian-type learning algorithm. A process control problem is presented and its control is investigated using the adaptation technique.

show abstract

Fuzzy Cognitive Maps: a model for intelligent supervisory control systems

Cited by 147 publications

References 13 publications

Tackling Travel Behaviour: An approach based on Fuzzy Cognitive Maps

Tackling Travel Behaviour: An approach based on Fuzzy Cognitive Maps

The challenge of using soft computing for decision support during labour

A Weight Adaptation Method for Fuzzy Cognitive Maps to a Process Control Problem

Contact Info

Product

Resources

About