A new method for rough measurement of the preference degree between action pairs in MCDM is presented based on the rough Sets theory.
提出一种多准则方案对偏好程度粗度量的一般方法。
The algorithm makes use of fuzzy-rough sets theory to describe its uncertainty degree and carries through its pre-processing with traditional methods according to the image's visual property.
该算法利用模糊粗糙集理论，依照图像的视觉特性，采用传统的图像增强方法进行图像预处理。
In the model, approximate quality difference of two evaluations in the same level is computed by rough sets, and the importance degree is determined by difference. The model is validated by instance.
应用粗糙集理论计算相同层次两两评价指标的近似质量差，根据差的大小确定指标重要性，并通过实例证明了该模型的合理性和正确性。
In the model, approximate quality difference of two evaluations in the same level is computed by rough sets, and the importance degree is determined by difference. The model is validated by instance.
应用粗糙集理论计算相同层次两两评价指标的近似质量差，根据差的大小确定指标重要性，并通过实例证明了该模型的合理性和正确性。
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