基于粗糙集-逼近理想解排序的辐射源威胁排序方法

将辐射源威胁评估作为多属性决策问题，提出逼近理想解排序（TOPSIS）法与粗糙集（RS）理论相结合的算法，构建一套完备的辐射源威胁等级排序模型，解决在没有先验信息条件下实时定量衡量辐射源威胁程度。针对TOPSIS方法中构造标准化决策矩阵时数据赋权的主观局限，运用粗糙集理论计算评价指标与评判结果的粗糙依赖度，确定评价指标权重，规避主观赋权的片面性。仿真结果与原始数据相符，证明所提方法的有效性，进一步量化威胁程度，有助于更精细准确排序。该方法具有工程实用价值，可以运用于辐射源威胁评估。

An Emitter Threat Evaluation Method Based on Rough Set and TOPSIS

The threat evaluation of emitters is regarded as a multi-attribute decision-making problem. A complete model for computing the threat metric values is established to realize the quantitative representation of the emitter threat degree, which is based on the rough set (RS) and technique for order preference by similarity to solution (TOPSIS), thus solving the problem of measuring emitter threat degree in real-time and quantitation without priori information. For the subjective limitation of structuring the standardized decision matrix in the process of determining the weights in TOPSIS, the RS theory is applied to compute the significance of evaluation indicators to obtain the weight coefficient, which is confirmed by calculating the rough dependability among evaluation indicators and evaluation results, avoiding the influence of subjective weight. The simulation result is consistent with the original data, which could prove the effectiveness of the proposed algorithm. In addition, the quantifiable threat function would contribute to assess and rank the threats more accurately. The results show that the proposed method has some practical value in engineering and could be used to evaluate the emitter threats.