基于直觉模糊Petri网的知识表示和推理

doi:10.3969/j.issn.0372-2112.2016.01.012

电子学报 ›› 2016, Vol. 44 ›› Issue (1): 77-86.DOI: 10.3969/j.issn.0372-2112.2016.01.012

基于直觉模糊Petri网的知识表示和推理

孟飞翔¹, 雷英杰¹, 余晓东¹, 雷阳²

1. 空军工程大学防空反导学院, 陕西西安 710051;
2. 武警工程大学, 陕西西安 710086

收稿日期:2014-07-15 修回日期:2015-02-11 出版日期:2016-01-25
- 作者简介:
- 孟飞翔 男,1986年11月出生,河南信阳人,现为空军工程大学计算机应用专业博士研究生,主要研究方向为智能信息处理. E-mail:ttimo@163.com 雷英杰 男,1956年11月出生,陕西华阴人,IEEE高级会员.现为空军工程大学教授,博士生导师,主要研究方向为智能信息处理与智能决策. E-mail:leiyjie@163.com
- 基金资助:
- 国家自然科学基金 (No.61272011); 国家自然科学青年基金 (No.61309022)

Knowledge Representation and Reasoning Using Intuitionistic Fuzzy Petri Nets

MENG Fei-xiang¹, LEI Ying-jie¹, YU Xiao-dong¹, LEI Yang²

1. Air and Missile Defense College, Air Force Engineering University, Xi'an, Shaanxi 710051, China;
2. Engineering University of Armed Police Force, Xi'an, Shaanxi 710086, China

Received:2014-07-15 Revised:2015-02-11 Online:2016-01-25 Published:2016-01-25

摘要/Abstract

摘要：

针对模糊Petri网存在隶属度单一的问题,将直觉模糊集理论与Petri网理论相结合,构建直觉模糊Petri网(Intuitionistic Fuzzy Petri Nets,IFPN)模型,用于知识的表示和推理.首先构建了IFPN模型,并将其应用于知识的表示,通过在模型中引入抑止转移弧,解决了否命题的表示问题.其次提出了基于矩阵运算的IFPN推理算法,通过修改变迁触发后token值的传递规则,解决了推理过程中的事实的保留问题;通过修改变迁的触发规则,抑制了变迁的重复触发.最后对推理算法进行了分析,并举例验证了提出的IFPN模型及其推理算法的可行性,结果表明IFPN是对FPN的有效扩充和发展,其对推理结果的描述更加细腻、全面.

关键词: 直觉模糊Petri网, 直觉模糊产生式规则, 知识表示, 直觉模糊推理

Abstract:

Aimed at fuzzy Petri nets (FPN) existing membership single issue, intuitionistic fuzzy Petri nets (IFPN) was constructed for knowledge representation and reasoning by combining intuitionistic fuzzy sets theory and Petri net theory.Firstly, IFPN model was constructed for knowledge representation, and the issue of negative proposition representation was solved by introducing inhibitive transfer arcs into the model.Secondly, the algorithm based on matrix operation was presented, the issue of fact reservation in reasoning procedure was solved by modifying token value's transfer rules after transitions being fired, and the issue of transitions repeatedly being fired was inhibited by modifying firing rules of transitions.Lastly, the algorithm was analyzed, and the feasibility of proposed IFPN model and algorithm was proved through an example.The result indicates that IFPN is an effective extension and development of FPN, and it describes the reasoning result more delicately and comprehensively.

Key words: intuitionistic fuzzy Petri nets (IFPN), intuitionistic fuzzy production rules, knowledge representation, intuitionistic fuzzy reasoning

中图分类号:

TP18

孟飞翔, 雷英杰, 余晓东, 雷阳. 基于直觉模糊Petri网的知识表示和推理[J]. 电子学报, 2016, 44(1): 77-86.

MENG Fei-xiang, LEI Ying-jie, YU Xiao-dong, LEI Yang. Knowledge Representation and Reasoning Using Intuitionistic Fuzzy Petri Nets[J]. Acta Electronica Sinica, 2016, 44(1): 77-86.

参考文献

[1] 鲍培明.基于BP网络的模糊Petri网的学习能力[J].计算机学报, 2004, 27(5):695-702. Bao Peiming.Learning capability in fuzzy Petri nets based on BP net[J].Chinese Journal of Computers, 2004, 27(5):695-702.(in Chinese)
[2] C G Looney.Fuzzy Petri nets for rule-based decision making[J].IEEE Transactions on Systems, Man, and Cybernetics, 1998, 18(1):178-183.
[3] Shyi-Ming Chen, Jyh-Sheng Ke, Jin-Fu Chang.Knowledge representation using fuzzy Petrinets[J].IEEE Transactions on Knowledge and Data Engineering, 1990, 2(3):311-319.
[4] Shyi-Ming Chen.Weighted fuzzy reasoning using weighted fuzzy Petri nets[J].IEEE Transactions on Knowledge and Data Engineering, 2002, 14(2):386-397.
[5] Meimei Gao, MengChu Zhou, Xiaoguang Huang, Zhiming Wu.Fuzzy reasoning Petri nets[J].IEEE Transactions on Systems, Man, and Cybernetics-Part A:Systems and Humans, 2003, 33(3):314-324.
[6] 汪洋, 林闯, 曲扬, 等.含有否定命题逻辑推理的一致性模糊Petri网模型[J].电子学报, 2006, 34(11):1955-1960. Wang Yang, Lin Chuang, Qu Yang, et al.Consistentfuzzy Petri nets model for logic programs with negation[J].Acta Electronica Sinica, 2006, 34(11):1955-1960.(in Chinese)
[7] 贾立新, 薛钧义, 茹峰.采用模糊Petri网的形式化推理算法及其应用[J].西安交通大学学报, 2003, 37(12):1263-1266. Jia Lixin, Xun Junyi, Ru Feng.Fuzzy Petri net based formalized reasoning algorithm with applications[J].Journal of Xi'an Jiaotong University, 2003, 37(12):1263-1266.(in Chinese)
[8] Xiaoou Li, Wen Yu, Felipe Lara-Rosano.Dynamic knowledge inference and learning under adaptive fuzzy Petri net framework[J].IEEE Transactions on Systems, Man, and Cybernetics-Part C:Applications and Reviews, 2000, 30(4):442-450.
[9] X Li, F Lara-Rosano.Adaptive fuzzy Petri nets for dynamic knowledge representation and inference[J].Expert Systems with Applications, 2000, 19:235-241.
[10] Hu-Chen Liu, Long Liu, Qing-Lian Lin, et al.Knowledge acquisition and representation using fuzzy evidential reasoning and dynamic adaptive fuzzy Petri nets[J].IEEE Transactions on Cybernetics, 2013, 43(3):1059-1072.
[11] Hu-Chen Liu, Qing-Lian Lin, Ling-Xiang Mao, et al.Dynamicadaptive fuzzy Petri nets for knowledge representation and reasoning[J].IEEE Transactions on Systems, Man, and Cybernetics:Systems, 2013, 43(6):1399-1410.
[12] Victor R L Shen.Knowledge representation using high-level fuzzy Petri nets[J].IEEE Transactions on Systems, Man, and Cybernetics-Part A:Systems and Humans, 2006, 36(6):2120-2127.
[13] Witold Pedrycz, Heloisa Camargo.Fuzzy timed Petri nets[J].Fuzzy Sets and Systems, 2003, 140:301-330.
[14] Feng Zhou, Roger J Jiao, Qianli Xu, et al.User experience modeling and simulation for product ecosystem design based on fuzzy reasoning Petri nets[J].IEEE Transactions on Systems, Man, and Cybernetics-Part A:Systems and Humans, 2012, 1(42):201-212.
[15] Jing Sun, Shi-Yin Qin, Yong-Hua Song.Faultdiagnosis of electric power systems based on fuzzy Petri nets[J].IEEE Transactions on Power Systems, 2004, 19(4):2053-2059.
[16] Atanassov K.Intuitionistic fuzzy sets[J].Fuzzy Sets and Systems, 1986, 20(1):87-96.
[17] Stephen JH Yang, Jeffrey JP Tsai, Chyun-Chyi Chen.Fuzzy rule base systems verification using high-level Petri nets[J].IEEE Transactions on Knowledge and Data Engineering, 2003, 15(2):457-473.
[18] Derek L Nazareth.Investigating the applicability of Petri nets for rule-based system verification[J].IEEE Transactions on Knowledge and Data Engineering, 1993, 4(3):402-410.

基于直觉模糊Petri网的知识表示和推理

Knowledge Representation and Reasoning Using Intuitionistic Fuzzy Petri Nets

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