An extended spiking neural P system for fuzzy knowledge representation

International Journal of Innovative Computing, Information and Control

Volumn 7, Issue 7 A, 2011, Pages 3709-3724

  Wang, Jun ^a   Zou, Li ^b   Peng, Hong ^a   Zhang, Gexiang ^c  

^a XIHUA UNIVERSITY   (China)

^b LIAONING NORMAL UNIVERSITY   (China)

^c SOUTHWEST JIAOTONG UNIVERSITY   (China)

Author keywords

Fuzzy number; Fuzzy production rules; Fuzzy reasoning; Fuzzy spiking neural P system

Indexed keywords

CERTAIN FACTOR; DISTRIBUTED AND PARALLEL COMPUTING; FUZZY INFORMATION; FUZZY KNOWLEDGE; FUZZY KNOWLEDGE REPRESENTATION; FUZZY NUMBERS; FUZZY PRODUCTION RULES; FUZZY REASONING; FUZZY REASONING PROCESS; NATURAL NUMBER; P SYSTEMS; RULE BASED SYSTEM; SPIKING NEURAL P SYSTEMS;

FUZZY RULES; KNOWLEDGE REPRESENTATION; PARALLEL ARCHITECTURES;

DISTRIBUTED COMPUTER SYSTEMS;

EID: 79959866425     PISSN: 13494198     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (24)

1. G. Paun, Computing with membranes, Journal of Computer and System Sciences, vol.61, no.1, pp.108-143, 2000.
2. G. Pǎun, Membrane Computing: An Introduction, Springer-Verlag Berlin Publishers, New York, 2002.
3. G. Pǎun and G. Rozenberg, A guide to membrane computing, Theor. Comput. Sci., vol.287, no.1, pp.73-100, 2002.
4. M. Ionescu, G. Pǎun and T. Yokomori, Spiking neural P systems, Fundameta Informaticae, vol.71, no.2-3, pp.279-308, 2006.
5. G. Pǎun, M. J. Pérez-Jiménez and G. Rozenberg, Spike train in spiking neural P systems, Int. J. Found. Comp. Sci., vol.17, no.4, pp.975-1002, 2006.
6. M. Ionescu, G. Pǎun and T. Yokomori, Spiking neural P systems with an exhaustive use of rules, Int. J. Unconvent. Comt., vol.3, no.2, pp.135-154, 2007.
7. J. Wang, H. J. Hoogeboom, L. Pan and G. Pǎun, Spiking neural P systems with weights and thresholds, The 10th Workshop on Membrane Computing, Romania, pp.514-533, 2009.
8. L. Pan and G. Pǎun, Spiking neural P systems with anti-spikes, Int. J. of Computers, Communications & Control, vol.4, no.3, pp.273-282, 2009.
9. A. Kaufmann and M. M. Gupta, Fuzzy Mathematical Models in Engineering and Management Science, Elsevier Science Publishers, New York, 1988.
10. S. M. Chen, A new approach to hangling fuzzy decisionmaking problems, IEEE Trans. on Syst. Man, Cybern., vol.18, no.6, pp.1012-1016, 1988.
11. S. M. Chen, J. S. Ke and J. F. Chang, Knowledge representation using fuzzy Petri nets, IEEE Trans. on Knowledge and Data Engineering, vol.2, no.3, pp.311-319, 1990.
12. L. A. Zadeh, Toward a theory of fuzzy information granulation and its centrality in human reasoning and fuzzy logic, Fuzzy Sets and Systems, vol.90, no.2, pp.111-127, 1997.
13. L. A. Zadeh, Toward a generalized theory of uncertainty (GTU) - An outline, Information Sciences, vol.172, pp.1-40, 2005.
14. L. A. Zadeh, Is there a need for fuzzy logic?, Information Sciences, vol.178, pp.2751-2779, 2008.
15. L. A. Zadeh, The concept of linguistic variable and its application to approximate reasoning, Part 1, 2, 3, Information Sciences, vol.8, no.9, pp.199-249, 301-357, 43-80, 1975.
16. L. A. Zadeh, Outline of a new approach to the analysis of complex systems and decision problems, IEEE Trans. on Systems, Cybernetics, vol.3, pp.28-44, 1973.
17. M. Mizumoto, S. Fukami and K. Tanaka, Some methods of fuzzy reasoning, in Advances in Fuzzy Set Theory and Applications (Norrth-Holland), M. M. Gupta, R. K. Ragade and R. R. Yager (eds.), Amsterdam, pp.117-136, 1979.
18. I. B. Turksan and Z. Zhong, An approximate analogical reasoning approach based on similarity measures, IEEE Trans. on Systems, Cybernetics, vol.18, pp.1049-1056, 1989.
19. T. Wang, Y. Chen and S. Tong, Fuzzy reasoning models and algorithms on type-2 fuzzy sets, International Journal of Innovative Computing, Information and Control, vol.4, no.10, pp.2451-2460, 2008.
20. M. Shimakawa, A proposal of extension fuzzy reasoning method, International Journal of Innovative Computing, Information and Control, vol.4, no.10, pp.2603-2616, 2008.
21. F.-T. Lin, Constraint scheduling problem with imprecise processing times using fuzzy numbers, ICIC Express Letters, vol.3, no.4B, pp.1465-1470, 2009.
22. L. Huang and I. H. Suh, Controller design for a marine diesel engine using membrane computing, International Journal of Innovative Computing, Information and Control, vol.5, no.4, pp.899-912, 2009.
23. J. Wang and H. Peng, Fuzzy knowledge representation based on an improving spiking neural P system, Proc. of the 6th International Conference on Natural Computation, Yantai, China, pp.3012-3015, 2010.
24. H. Peng and J. Wang, Adaptive spiking neural P systems, Proc. of the 6th International Conference on Natural Computation, Yantai, China, pp.3008-3011, 2010.