Abstract
The fuzzy cognitive maps [1–6] are qualitative tools which can capture the extent from cause to effect in the links that exist within a complex system such as the information system. These cognitive maps are a simple way of representing knowledge with a huge capacity of interpreting the information. Indeed, they are exploited for the decision-making, the prediction of future states and the explanation of past actions. Added to these capacities, when the information is applied and propagated through the model, the topology of the map itself can be used in the diagnosis of breakdowns by identifying the causes of the nodes of interest [7]. The main objective of this paper is the conception of impact analysis of engine of rules in an environment object in which objects and their links of impact (CIs: elementary components of the information system contributing to the delivery of a service), are neither defined nor ordered and the real time restoration of analysis of impact results and presentation according to the various orchestrated processes. Thus our role is to conceive a design of impact analysis and its development guaranteeing in times of answer by using the inference of the fuzzy cognitive maps.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Julie, A., Kosko, B.: Virtual worlds as fuzzy cognitive maps. In: Virtual Reality Annual International Symposium, vol. 12, pp. 471–477 (1993)
Tsadiras, A.K.: Comparing the inference capabilities of binary, trivalent and sigmoid fuzzy cognitive maps. Inf. Sci. 178, 3880–3894 (2008)
Kosko, B.: Fuzzy cognitive maps. Int. J. Man Mach. Stud. 24, 65–75 (1986)
Stylios, C.D., Georgopoulos, V.C., Malandraki, G.A., Chouliara, S.: Fuzzy cognitive map architecture for medical decision support systems. Appl. Soft Comput. 8, 1243–1251 (2008)
Pelaez, C.E., Bowles, J.B.: Using fuzzy cognitive maps as a system model for failure modes and effects analysis. Inf. Sci. 88, 177–199 (1996)
Yaman, D., Polat, S.: A fuzzy cognitive map approach for effect-based operations: An illustrative case. Inf. Sci. 179, 382–403 (2009)
Pagageorgiou, E.I., Spyridonos, P.P., Glotsos, D.T., Stylios, C.D., Ravazoula, P., Nikiforidis, G.N., Groumpos, P.P.: Brain tumor characterization using the soft computing technique of fuzzy cognitive maps. Appl. Soft Comput. 8, 820–828 (2008)
Perusich, K.: Using fuzzy cognitive maps to identify multiple causes in troubleshooting systems. Integr. Comput. Aided Eng 15, 197–206 (2008)
Perusich, K.: Using fuzzy maps to assess multi-operator situation awareness. In: Collaborative Crew Performance in Complex Operational Systems, pp. 20–22 (1998)
Lee, K.C., Kim, J.S., Chung, N.H., Kwon, S.J.: Fuzzy cognitive map approach to web-mining inference amplification. Expert Syst. Appl. 22, 197–211 (2002)
Lee, K.C., Lee, S.: Causal knowledge-based design of EDI controls: an explorative study. Comput. Hum. Behav. 23, 628–663 (2007)
Chunmei, L.: Combination study of fuzzy cognitive map. Int. J. Energ. Environ. 1, 65–69 (2007)
Rodriguez-Repiso, L., Setchi, R., Salmeron, J.L.: Modelling IT project success with fuzzy cognitive maps. Expert Syst. Appl. 32, 543–559 (2007)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer International Publishing Switzerland
About this paper
Cite this paper
Lassoued, F., Bouallegue, R. (2016). A Fault Tolerance Mechanism in Distributed and Complex System on a LAN. In: El Oualkadi, A., Choubani, F., El Moussati, A. (eds) Proceedings of the Mediterranean Conference on Information & Communication Technologies 2015. Lecture Notes in Electrical Engineering, vol 381. Springer, Cham. https://doi.org/10.1007/978-3-319-30298-0_58
Download citation
DOI: https://doi.org/10.1007/978-3-319-30298-0_58
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-30296-6
Online ISBN: 978-3-319-30298-0
eBook Packages: EngineeringEngineering (R0)