基于模糊集和粗糙集的武器系统作战能力评估

为了解决多属性决策中各属性权值常依赖主观确定的问题，提出了一种基于模糊集和连续粗糙集的武器系统作战能力评价模型。对连续系统样本值归一化后，采用模糊偏序模型对各样本进行排序，建立连续值决策信息表，解决了一般粗糙集需要有决策信息表的问题。进而基于粗糙集属性的广义重要度，计算各属性值的权重系数，避免了因属性值离散化对噪声的敏感而造成的不良后果。结合战斗机空战能力评估，验证了该方法对武器系统作战能力评估的可行性和有效性。

Campaign capability evaluation of weapon systems based on fuzzy sets and rough sets

To solve the problem that weight of each attribute is usually determined subjectively in multiattribute decision making, a new model based on fuzzy sets and rough sets is proposed to assess the campaign  capability of weapon systems. Sample values having been normalized, each sample is ranked by a fuzzy  partial rank model. A decision making information list of continuous values is built so as to solve the problem that there must be a decision-making information list in general rough sets. Then the weight coefficient of each attribute value is calculated based on generalized importance of attribute to avoid the bad aftereffect worked by dispersing attribute  values sensitized to noise. Combining with an air combat ability assessment of fighters, the feasibility and validity of weapon systems’ campaign capability assessment by this method are verified.