Abstract:
Fuzzy cognitive maps (FCMs) represent a means of fuzzy causal knowledge processing, using the net rather than the traditional tree knowledge representation. The FCM appro...Show MoreMetadata
Abstract:
Fuzzy cognitive maps (FCMs) represent a means of fuzzy causal knowledge processing, using the net rather than the traditional tree knowledge representation. The FCM approach allows various knowledge bases to be combined. Similarities between the FCMs and signal flow graphs (SFGs) are pointed out and the inference process used in FCMs is compared in parallel with a fixed point iterative solution of the equations describing the SFG. Then, applications to qualitative circuit analysis are discussed for a class of feedback amplifiers and general active RLC circuits, using a combination of the SFG and FCM concepts. Several examples are given.<>
Published in: IEEE 1988 International Conference on Neural Networks
Date of Conference: 24-27 July 1988
Date Added to IEEE Xplore: 06 August 2002
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Cites in Papers - IEEE (14)
Select All
1.
A. Senkov, "Intelligent Software Platform and End-Point Software for Risk Management", 2018 International Multi-Conference on Industrial Engineering and Modern Technologies (FarEastCon), pp.1-5, 2018.
2.
Amr El-Mougy, Mohamed Ibnkahla, Ghaith Hattab, Waleed Ejaz, "Reconfigurable Wireless Networks", Proceedings of the IEEE, vol.103, no.7, pp.1125-1158, 2015.
3.
Beatrice Lazzerini, Lusine Mkrtchyan, "Analyzing Risk Impact Factors Using Extended Fuzzy Cognitive Maps", IEEE Systems Journal, vol.5, no.2, pp.288-297, 2011.
4.
Yuan Miao, ChunYan Miao, XueHong Tao, ZhiQi Shen, ZhiQiang Liu, "Transformation of Cognitive Maps", IEEE Transactions on Fuzzy Systems, vol.18, no.1, pp.114-124, 2010.
5.
Yuan Miao, "A Software Agent Based Simulation Model for Systems with Decision Units", 2009 Eighth IEEE International Conference on Dependable, Autonomic and Secure Computing, pp.270-275, 2009.
6.
Y.G. Petalas, K.E. Parsopoulos, E.I. Papageorgiou, P.P. Groumpos, M.N. Vrahatis, "Enhanced Learning in Fuzzy Simulation Models Using Memetic Particle Swarm Optimization", 2007 IEEE Swarm Intelligence Symposium, pp.16-22, 2007.
7.
Yuan Miao, XueHong Tao, ZhiQi Shen, ZhiQiang Liu, ChunYan Miao, "The Equivalence of Cognitive Map, Fuzzy Cognitive Map and Multi Value Fuzzy Cognitive Map", 2006 IEEE International Conference on Fuzzy Systems, pp.1872-1878, 2006.
8.
D. Grant, K.-M. Osei-Bryson, "Using Fuzzy Cognitive Maps to Assess MIS Organizational Change Impact", Proceedings of the 38th Annual Hawaii International Conference on System Sciences, pp.263c-263c, 2005.
9.
M. Parenthoen, P. Reignier, J. Tisseau, "Put fuzzy cognitive maps to work in virtual worlds", 10th IEEE International Conference on Fuzzy Systems. (Cat. No.01CH37297), vol.1, pp.252-255 vol.1, 2001.
10.
R. Taber, R.R. Yager, C.M. Helgason, "Small-sample quantization effects on the equilibrium behavior of combined fuzzy cognitive maps", 10th IEEE International Conference on Fuzzy Systems. (Cat. No.01CH37297), vol.3, pp.1567-1572 vol.2, 2001.
11.
D.E. Koulouriotis, I.E. Diakoulakis, D.M. Emiris, "Learning fuzzy cognitive maps using evolution strategies: a novel schema for modeling and simulating high-level behavior", Proceedings of the 2001 Congress on Evolutionary Computation (IEEE Cat. No.01TH8546), vol.1, pp.364-371 vol. 1, 2001.
12.
N. Bryson, A. Mobolurin, A. Joseph, "Generating consensus fuzzy cognitive maps", Proceedings Intelligent Information Systems. IIS'97, pp.231-235, 1997.
13.
P.C. Silva, "Fuzzy cognitive maps over possible worlds", Proceedings of 1995 IEEE International Conference on Fuzzy Systems., vol.2, pp.555-560 vol.2, 1995.
14.
J.J. Farah, R.B. Kelley, "Identifying relational error recovery/online plans utilizing fuzzy logic techniques and semantic networks", Proceedings of 1993 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS '93), vol.3, pp.1736-1741 vol.3, 1993.
Cites in Papers - Other Publishers (19)
1.
Nabin Sapkota, Waldemar Karwowski, Advances in Artificial Intelligence, Software and Systems Engineering, vol.787, pp.391, 2019.
2.
O. Motlagh, Z. Jamaludin, S. H. Tang, W. Khaksar, "An agile FCM for real-time modeling of dynamic and real-life systems", Evolving Systems, vol.6, no.3, pp.153, 2015.
3.
Omid Motlagh, Tang Sai Hong, Sayed Mahdi Homayouni, George Grozev, Elpiniki I. Papageorgiou, "Development of application-specific adjacency models using fuzzy cognitive map", Journal of Computational and Applied Mathematics, vol.270, pp.178, 2014.
4.
Lusine Mkrtchyan, Da Ruan, Handbook on Decision Making, vol.33, pp.39, 2012.
5.
DA RUAN, FRANK HARDEMAN, LUSINE MKRTCHYAN, "A NOVEL APPROACH FOR SAFETY CULTURE ASSESSMENT", International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, vol.20, no.supp01, pp.1, 2012.
6.
Elpiniki I. Papageorgiou, Cross-Disciplinary Applications of Artificial Intelligence and Pattern Recognition, pp.583, 2012.
7.
Yuan Miao, Advances in Practical Multi-Agent Systems, vol.325, pp.63, 2010.
8.
E. Parsopoulos Konstantinos, N. Vrahatis Michael, Particle Swarm Optimization and Intelligence, pp.149, 2010.
9.
Y. G. Petalas, K. E. Parsopoulos, M. N. Vrahatis, "Improving fuzzy cognitive maps learning through memetic particle swarm optimization", Soft Computing, vol.13, no.1, pp.77, 2009.
10.
Moon-Chan Kim, Chang Ouk Kim, Seong Rok Hong, Ick-Hyun Kwon, "Forward–backward analysis of RFID-enabled supply chain using fuzzy cognitive map and genetic algorithm", Expert Systems with Applications, vol.35, no.3, pp.1166, 2008.
11.
Kun-Chang Lee, Soonjae Kwon, Intelligent Decision-making Support Systems, pp.167, 2006.
12.
Uygar Özesmi, Stacy L. Özesmi, "Ecological models based on people’s knowledge: a multi-step fuzzy cognitive mapping approach", Ecological Modelling, vol.176, no.1-2, pp.43, 2004.
13.
Inwon Kang, Sangjae Lee, Jiho Choi, "Using fuzzy cognitive map for the relationship management in airline service", Expert Systems with Applications, vol.26, no.4, pp.545, 2004.
14.
Sangjae Lee, Byung Gon Kim, Kidong Lee, "Fuzzy cognitive map-based approach to evaluate EDI performance: a test of causal model", Expert Systems with Applications, vol.27, no.2, pp.287, 2004.
15.
Kweku-Muata Osei-Bryson, "Generating consistent subjective estimates of the magnitudes of causal relationships in fuzzy cognitive maps", Computers & Operations Research, vol.31, no.8, pp.1165, 2004.
16.
Veerendra-Kumar Rai, Dong-Hwan Kim, "Principal–agent problem: a cognitive map approach", Electronic Commerce Research and Applications, vol.1, no.2, pp.174, 2002.
17.
Sangjae Lee, Ingoo Han, "Fuzzy cognitive map for the design of EDI controls", Information & Management, vol.37, no.1, pp.37, 2000.
18.
Noel (Kweku-Muata) Bryson, Ayodele Mobolurin, "A process for generating quantitative belief functions", European Journal of Operational Research, vol.115, no.3, pp.624, 1999.
19.
"REFERENCES", Neural Network PC Tools, pp.321, 1990.