Adaptive fuzzy cognitive maps vs neutrosophic cognitive maps: Decision support tool for knowledge based institutions

Journal of Scientific and Industrial Research

Volumn 67, Issue 9, 2008, Pages 665-673

  Banerjee, Goutam ^a  

^a JADAVPUR UNIVERSITY   (India)

Author keywords

Decision support systems; Fuzzy cognitive maps (FCM); Neutrosophic cognitive maps (NCM)

Indexed keywords

COGNITIVE SYSTEMS; DECISION SUPPORT SYSTEMS; FUZZY SETS;

DECISION SUPPORT SYSTEM; FUZZY MATHEMATICS; MAP;

EID: 55349116705     PISSN: 00224456     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (35)

1. Wiig K, Knowledge Management Foundations: Thinking about Thinking - How People and Organizations Create, Represent and Use Knowledge (Schema Press, Texas) 1993, 471.
2. Courtney J F, Decision making and knowledge management in inquiring organizations: toward a new decision-making paradigm for DSS, Decision Support Syst, 31 (2001) 17-38.
3. Haeley P, Exploring synergies between knowledge management and case based reasoning, in American Association for Artificial Intelligence Workshop (American Association for Artificial Intelligence, California) 18-19 July 1999.
4. Noh J B, Lee K C, Kim J K, Lee J K & Kim S H A case based reasoning approach to cognitive map-driven tacit knowledge management, J Expert System Applications, 19 (2000) 249-259.
5. Smith R G & Farquhar A, The road ahead for knowledge management: An AI perspective, Winter, 21 (2000) 17-40.
6. Liebowitz J, Building Organizational Intelligence: A Knowledge Management Primer (CRC Press, ca Raton, Florida) 2000, 160.
7. Metaxiotis K, Ergazakis K, Samouilidis E & Psarras J, Decision support through knowledge management: the role of the artificial intelligence, Inform Manage & Compu Security, 11 (2003) 216-221.
8. Walsh J P & Ungson G R, Organizational memory, Acad Manage Rev, 16 (1991) 57-91
9. Bannon L J & Kuutti K, Shifting perspectives on organizational memory: from storage to active remembering, in Proc. 29th Hawaii Int Conf Syst Sci (Institute of Electrical and Electronics Engineers, Wailea, HI, USA) 1996, 156-167.
10. Guerrero L A & Pino Jose A, Understanding organizational memory, Interact Compu, 8 (1996) 299-310.
11. Huber G P, A theory of the effects of advanced information technologies on organizational design, intelligence and decision making, Acad Manage J, 15 (1990) 47-71.
12. Nonaka I, A dynamic theory of organizational knowledge creation, Org Sci, 5 (1994) 14-37
13. Bhatt G D & Zaveri J, The enabling role of decision support systems in organization learning, Decision Support Syst, 32 (1997) 297-309.
14. Axelrod R, Structure of Decision: The Cognitive Maps of Political Elites (Princton University Press, New Jersey) 1976, 404.
15. Kosko B, Differential Hebbian learning, in Proc AIP Conf 151 (American Institute of Physics, New York) 1986, 265-270.
16. Kosko B, Fuzzy cognitive maps, Int J Man-Machine Stud, 24 (1986) 65-75.
17. Kosko B, Hidden patterns in combined and adaptive knowledge networks, Int J Approx Reason, 2 (1988) 377-393.
18. Kosko B, Neural Networks and Fuzzy Systems (Prentice Hall, New Jersey) 1992, 480-p.
19. Kosko B, Fuzzy Engineering (Prentice Hall, New Jersey) 1997, 549p.
20. Klir G J & Folger T A, Fuzzy Sets, Uncertainty And Information (Prentice Hall, New Delhi) 1991, 65406.
21. Kang I, Lee S & Choi J, Using fuzzy cognitive map for the relationship management in airline service, Expert Syst Applications, 24 (2004) 545-555.
22. Xirogiannis G & Glykas M, Fuzzy cognitive maps in business analysis and performance-driven change, IEEE Trans Eng Manage, 51 (2004) 334-351.
23. Lee K C & Kim H S, A fuzzy cognitive map based bidirectional inference mechanism: an application to stock investment analysis, J Intelligent Syst Accounting, Finance & Manage, 6 (1997) 41-57.
24. Xirogiannis G, Glykas M & Staikouras C, Fuzzy cognitive maps as a back end to knowledge-based systems in geographically dispersed financial organizations, Knowledge Process Manage, 11 (2004). 137-154,
25. Papageorgiou E, Stylios C D & Groumpos P P, Fuzzy cognitive map learning based on nonlinear Hebbian rule, in 16th Australian Confon Artificial Intelligence (Perth, Australia) 3-5 December 2003.
26. Papageorgiou E, Stylios C D & Groumpos P P, Active Hebbian learning algorithm to train fuzzy cognitive maps, Int J Approx Reason, 37 (2004)219-249.
27. Stach W, Kurgan L, Pedrycz W & Reformat M, Genetic learning of fuzzy cognitive maps, Fuzzy Sets Syst, 153 (2005) 371-401.
28. Papageorgiou E L, Stylios C & Groumpos P P, Unsupervised learning techniques for fine-tuning fuzzy cognitive map causal links, Int J Human-Compu Stud, 64 (2006) 727-743.
29. Hebb D O, The Organization of Behavior, 12th edn (Wiley, New York) 1949, 378.
30. Dickerson J & Kosko B, Virtual worlds as fuzzy cognitive maps, Presence, 3 (1994) 173-189.
31. Khan M S & Quaddus M, Group decision support using fuzzy cognitive maps for casual reasoning, Group Decision Negotiation, 13 (2004) 463-480.
32. Khan M S, Chong A & Gredeon T, A methodology for developing adaptive fuzzy cognitive maps for decision support, J Adv Compu Intelligence & Intelligent Informatics, 4 (2000) 403-407.
33. Banerjee G, Roadmapping in R&D: A neuro-fuzzy thinking, in Proc Int Conf Innovation and Technology Management (Indian Association for Productivity, Quality and Reliability & Central Glass & Ceramic Research Institute, Kolkata) 2006, 281-291.
34. Samarandche F, Definitions derived from neutrosophics, in Proc First Int Conf Neutrosophy, Neutrosophic Logic, Neutrosophic Set, Neutrosophic Probability and Statistics (University of New Mexico, Gallup) 1-3 December 2001.
35. Vasanthakaudaswamy, W B & Samarandche F, Fuzzy Cognitive Maps and Neutrosophic Cognitive Maps (Xiquan, Phoenix) 2003, 123-190.