基于自适应直觉模糊推理的威胁评估方法
doi: 10.3724/SP.J.1146.2006.00708
Techniques for Threat Assessment Based on Adaptive Intuitionistic Fuzzy Reasoning
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摘要: 将直觉模糊集理论引入信息融合领域,提出一种基于自适应直觉模糊推理的威胁评估方法。首先,分析了现有威胁评估方法的特点与局限性,建立了基于自适应神经-直觉模糊推理系统(ANIFIS)的Takagi-Sugeno型威胁评估模型。其次,设计了系统变量的属性函数和推理规则,确定了各层输入输出的计算关系,以及系统输出结果的合成计算表达式。再次,分析了模型的全局逼近性,设计了网络学习算法。最后,以20批典型目标的威胁评估为例,给出相应的评估结果,验证了方法的有效性和模型的正确性。实践结果表明,该方法可以提高威胁评估的可信度,改进评估质量,提高推理结果综合值的精度。Abstract: To the issues of threat assessment (TA), a technique for TA based on Adaptive Neuro-Intuitionistic Fuzzy Inference System (ANIFIS) is proposed with intuitionistic fuzzy set theory introduced into the area of information fusion. First, the properties and vulnerabilities of the existing TA methods are analyzed. A model for TA on ANIFIS with Takagi-Sugeno type is established. Then, the attribute functions, i.e. membership and nonmembership 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. Subsequently, an analysis of global approximation property of the model is performed with a learning algorithm of neural net devised. Finally, the validity of the technique is checked and rationality of constructed model is verified by providing TA instances with 20 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.
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