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    广义多尺度集值决策系统最优尺度选择

    Optimal Scale Selection for Generalized Multi-Scale Set-Valued Decision Systems

    • 摘要: 为了在不同的粒度下对同一对象进行观察、表示、分析和决策,提出了多尺度信息系统.考虑到一个对象在属性的各个尺度上的取值为多值的情况,多尺度信息系统被进一步扩展到多尺度集值信息系统.然而,在现有的多尺度集值信息系统中,所有属性必须具有相同的尺度级数,使得每个属性都只能在同一个尺度下进行组合.并且,最优尺度选择仅考虑决策系统的一致性或不确定性,忽略了实际应用中的决策代价问题.针对上述问题,定义了一种具有代价的广义多尺度集值决策系统,分析了决策系统的不确定性和代价随尺度组合的变化趋势.然后,为了提高最优尺度选择的时间效率,提出了一种基于三支决策思想的尺度空间更新方法.最后,结合用户需求,给出了最小化不确定性和代价的最优尺度选择方法.实验结果表明,该方法不仅可以结合不确定性和代价得到最优尺度解,并且与传统的Lattic Mode相比,能有效地提高计算效率.

       

      Abstract: In order to observe, represent, analyze and make decisions on the same object at different granularity, multi-scale information system is proposed. Considering that the value of an object in each scale of attribute is multiple, multi-scale information system is further extended to multi-scale set-valued information system. However, existing researches on multi-scale set-valued information systems assume that all attributes must have the same number of scales, and this assumption makes all attributes can only be combined at the same scale. Moreover, the optimal scale only considers the consistency or uncertainty of the decision system, and ignores the cost of practical application. To solve the above problems, a generalized multi-scale set-valued decision system with cost is defined, and the variation trend of uncertainty and the cost of decision system with different scale combinations is analyzed. Then, in order to improve the time efficiency, a scale space updating method based on three-way decisions is proposed. Finally, an optimal scale selection method is proposed to minimize the uncertainty and cost based on users’ requirement. The experimental results show that the proposed method can not only obtain the optimal scale by combining the uncertainty and cost, but also effectively improve the computational efficiency compared with the method of lattic mode (LM).

       

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