【摘要】 针对属性权重完全未知且属性值以专家经验给出的多属性决策问题,提出了利用属性重要度计算权重的分配方法。根据粗糙集中的相对正域概念,探讨了如何运用属性重要度确定各属性的权重。将权重确定问题转化为粗糙集中属性重要性评价问题,建立了关于风险评价的关系数据模型,经过属性值特征化建立了知识系统,在数据分析下通过分析评判方法对评价对象的支持度和重要性,计算出风险评价模型的权重。该方法克服了传统权重确定方法的主观性,使得风险评价方法更具客观性,从而提高了火灾危险源风险评价的精度,通过实例说明该方法更加有效合理。更多还原

【Abstract】 Aiming at the information about the attribute weights in unknown completely and the attribute values relied on expert experience,the author puts forward an weight allocation method based on importance of attribute in multi-attribute decision-making.This method discusses how to ascertain the weight allocation by applying the attribute importance based on the relative positive region conception.Determining weight is translated into estimating significance of attributes among rough sets.A relation data model about risk assessment is established.Knowledge systems are built through making attribute value into eigenvalue.In the data analyzsis,the weight of a risk assessment model is computed by analyzing the support and significance of forecasting method for the predicted object.The proposed approach overcomes the subjectivity of traditional determination to weight,and makes risk assessment more objective,thus improving the precision of risk assessment for fire hazard.At last,an example is given to show the methods more effective and rational than before.更多还原