NDLI: Threat Assessment Based on Adaptive Intuitionistic Fuzzy Neural Network

Content Provider	IEEE Xplore Digital Library
Author	Fang Yihong Li Weimin Zhou Xiaoguang Xie Xin
Copyright Year	2011
Abstract	This paper proposes a method for threat assessment(TA) based on Adaptive Intuitionistic Fuzzy Neural Network(AIFNN). Firstly, intuitionistic fuzzy proposition is defined and the concept of intuitionistic fuzzy reasoning is discussed and Takagi-Sugeno Kang intuitionistc fuzzy model is developed. Secondly, a model for TA on AIFNN based on Takagi-Sugeno Takagi-Sugeno Kang intuitionistc fuzzy model is established, the attribute functions, ie. membership and non-membership functions, and the inference rules of the system variables are devised with computational relations between layers of input and output and a synthesized computational expression of system outputs ascertained. Thirdly, a learning algorithm of neural based on the extended kalman algorithm is designed. Finally, the validity of the technique is checked and rationality of constructed model is verified by providing TA instances with 400 typical targets. The simulated results show that this method can enhance creditability of TA and improve quality of assessment with precision of synthetic values in reasoning output.
Starting Page	262
Ending Page	265
File Size	376860
Page Count	4
File Format	PDF
ISBN	9781457710858
DOI	10.1109/ISCID.2011.73
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-10-28
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Jacobian matrices Fuzzy logic Algorithm design and analysis Fuzzy sets Equalizers Intuitionistic Fuzzy Set Adaptive Intuitionistic Fuzzy Neural Networks Extended Kalman Algorithm Kalman filters Threat Assessment Pragmatics
Content Type	Text
Resource Type	Article

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