Modeling Complex Systems Using Fuzzy Cognitive Maps

Stylios, Chrysostomos; Groumpos, Peter P.

doi:10.1109/tsmca.2003.818878

Cited by 386 publications

(186 citation statements)

References 14 publications

Supporting

Mentioning

179

Contrasting

Unclassified

Order By: Relevance

“…However, in contrast to FCM, none of these techniques is able to model the influence of the different states/events in the overall system. FCMs have been previously described and used in [4,7] to model human knowledge, together with new and unseen behaviours of particular scenarios. The authors of [4] provide a detailed description of the FCM and its mathematical foundation.…”

Section: Related Workmentioning

confidence: 99%

“…FCMs have been previously described and used in [4,7] to model human knowledge, together with new and unseen behaviours of particular scenarios. The authors of [4] provide a detailed description of the FCM and its mathematical foundation. The authors in [7] provide a detailed description of an FCM and examples that use an FCM to model fault propagation in interconnected systems.…”

Section: Related Workmentioning

confidence: 99%

“…We have empirically chosen the limit cycle t = 60. A more detailed description of FCM models can be found in [4].…”

Section: A Fuzzy Cognitive Mapmentioning

confidence: 99%

“…In order to incorporate the PoL into the detection process, a Fuzzy Cognitive Map (FCM) [4] can be used in conjunction with our anomaly-based IDS. An FCM provides a useful framework to represent the behaviour of a system and to calculate the degree of influence that one event or action may have upon the whole system and upon parts of the system.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Using the pattern-of-life in networks to improve the effectiveness of intrusion detection systems

Aparicio-Navarro

Chambers

Kyriakopoulos

et al. 2017

2017 IEEE International Conference on Communications (ICC)

View full text Add to dashboard Cite

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

“…We have empirically chosen the limit cycle t = 60. A more detailed description of FCM models can be found in [4].…”

Section: A Fuzzy Cognitive Mapmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Using the pattern-of-life in networks to improve the effectiveness of intrusion detection systems

Aparicio-Navarro

Chambers

Kyriakopoulos

et al. 2017

2017 IEEE International Conference on Communications (ICC)

View full text Add to dashboard Cite

“…In supervised mode 7 , the target output of the domain is fixed in advance while in the unsupervised mode the domain target is not fixed. In the present research, the target output is fixed and estimated.…”

Section: Evaluation Of Strategymentioning

confidence: 99%

Fuzzy Cognitive Maps for Identifying Critical Path in Strategic Domains

Banerjee¹

2009

DSJ

View full text Add to dashboard Cite

Fuzzy cognitive maps (FCM) are hybrid tools of artificial neural network and fuzzy logic systems. One of their major uses is in decision support systems. To arrive at correct decisions, the fuzzy interconnections between attributes are either trained or assigned by domain experts. The network target may be fixed or unknown. In this paper, the FCM has been illustrated in a strategic domain in which the target is fuzzily defined and unknown. The target value is therefore estimated first by fuzzy inference rules for a collection of imprecisely defined attributes and then the fuzzy gradation to which the value belongs is used as the basis to tune the cognitive map The domain concerns a research institution. The target risk is the time by which the projects run-off beyond the stipulated time of completion. The paper shows that certain instinctively chosen membership functions to tune the cognitive map are able to reproduce the belief surrounding the criticality of the domain.

show abstract

Causal mapping as a tool to mechanistically interpret phenomena in cell motility: Application to cortical oscillations in spreading cells

Weinreb¹,

Elston²,

Jacobson³

2006

Cell Motil. Cytoskeleton

View full text Add to dashboard Cite

Biological processes that occur at the cellular level and consist of large numbers of interacting elements are highly nonlinear and generally involve multiple time and spatial scales. The quantitative description of these complex systems is of great importance but presents large challenges. We outline a new systems biology approach, causal mapping (CMAP), which is a coarse-grained biological network tool that permits description of causal interactions between the elements of the network and overall system dynamics. On one hand, the CMAP is an intermediate between experiments and physical modeling, describing major requisite elements, their interactions and paths of causality propagation. On the other hand, the CMAP is an independent tool to explore the hierarchical organization of cell and the role of uncertainties in the system. It appears to be a promising easy-to-use technique for cell biologists to systematically probe verbally formulated qualitative hypotheses. We apply the CMAP to study the phenomenon of contractility oscillations in spreading cells in which microtubules have been depolymerized. The precise mechanism by which these oscillations are governed by a complex mechano-chemical system is not known but the data observed in experiments can be described by a CMAP. The CMAP suggests that the source of the oscillations results from the opposing effects of Rho activation leading to a decreased level of myosin light chain phosphatase and a cyclic calcium influx caused by increased membrane tension and leading to a periodically enhanced activation of myosin light chain kinase.

show abstract

Modeling Complex Systems Using Fuzzy Cognitive Maps

Cited by 386 publications

References 14 publications

Using the pattern-of-life in networks to improve the effectiveness of intrusion detection systems

Using the pattern-of-life in networks to improve the effectiveness of intrusion detection systems

Fuzzy Cognitive Maps for Identifying Critical Path in Strategic Domains

Causal mapping as a tool to mechanistically interpret phenomena in cell motility: Application to cortical oscillations in spreading cells

Contact Info

Product

Resources

About