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2011 Fourth International Symposium on Computational Intelligence and Design
Threat Assessment Based on Adaptive Intuitionistic Fuzzy Neural Network
Hangzhou, China
October 28-October 30
ISBN: 978-0-7695-4500-4
| ASCII Text | x | ||
| Fang Yihong, Li Weimin, Zhou Xiaoguang, Xie Xin, "Threat Assessment Based on Adaptive Intuitionistic Fuzzy Neural Network," Computational Intelligence and Design, International Symposium on, vol. 1, pp. 262-265, 2011 Fourth International Symposium on Computational Intelligence and Design, 2011. | |||
| BibTex | x | ||
| @article{ 10.1109/ISCID.2011.73, author = {Fang Yihong and Li Weimin and Zhou Xiaoguang and Xie Xin}, title = {Threat Assessment Based on Adaptive Intuitionistic Fuzzy Neural Network}, journal ={Computational Intelligence and Design, International Symposium on}, volume = {1}, year = {2011}, isbn = {978-0-7695-4500-4}, pages = {262-265}, doi = {http://doi.ieeecomputersociety.org/10.1109/ISCID.2011.73}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, } | |||
| RefWorks Procite/RefMan/Endnote | x | ||
| TY - CONF JO - Computational Intelligence and Design, International Symposium on TI - Threat Assessment Based on Adaptive Intuitionistic Fuzzy Neural Network SN - 978-0-7695-4500-4 SP262 EP265 A1 - Fang Yihong, A1 - Li Weimin, A1 - Zhou Xiaoguang, A1 - Xie Xin, PY - 2011 KW - Threat Assessment KW - Intuitionistic Fuzzy Set KW - Adaptive Intuitionistic Fuzzy Neural Networks KW - Extended Kalman Algorithm VL - 1 JA - Computational Intelligence and Design, International Symposium on ER - | |||
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ISCID.2011.73
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.
Index Terms:
Threat Assessment, Intuitionistic Fuzzy Set, Adaptive Intuitionistic Fuzzy Neural Networks, Extended Kalman Algorithm
Citation:
Fang Yihong, Li Weimin, Zhou Xiaoguang, Xie Xin, "Threat Assessment Based on Adaptive Intuitionistic Fuzzy Neural Network," iscid, vol. 1, pp.262-265, 2011 Fourth International Symposium on Computational Intelligence and Design, 2011
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