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This paper presents a fuzzy spiking neural P system (FSN P system) to represent the fuzzy production rules in a knowledge base of a rule-based system, where the certainty factors of fuzzy production rules and the truth values of propositions are described by trapezoidal fuzzy numbers. In the proposed FSN P system, the definition of traditional neurons has been extended. The neurons are divided into two types: proposition neurons and rule neurons; the content of each neuron is a trapezoidal fuzzy number in instead of an integer. Also the fuzzy reasoning process can be modeled by the proposed FSN P system.
Published in:
Bio-Inspired Computing: Theories and Applications (BIC-TA), 2010 IEEE Fifth International Conference on
Date of Conference: 23-26 Sept. 2010
- Page(s):
- 586 - 590
- Print ISBN:
- 978-1-4244-6437-1
- INSPEC Accession Number:
- 11684338
- Conference Location :
- Changsha
- Digital Object Identifier :
- 10.1109/BICTA.2010.5645191
- Product Type:
- Conference Publications
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