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A method on post-evaluation of whole staff performance management based on fuzzy partial ordering and rough sets

机译:基于模糊偏序和粗糙集的全员绩效管理后评价方法

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To solve the problem that weights of each attribute of whole staff performance management are often determined subjectively in multi-attribute assessment A whole staff performance management evaluation model based on fuzzy partial ordering and rough set theory is proposed. 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 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 and to overcome the problem that general rough sets are difficult to be used in continuous attributes, which have non-commensurability, variation range and strong antagonism. Then, the feasibility and validity of post-evaluation of whole staff performance management is verified by fuzzy partial ordering and rough sets method.
机译:为解决多属性评估中往往会主观确定整个员工绩效管理各个属性的权重的问题,提出了一种基于模糊偏序和粗糙集理论的员工整体绩效管理评价模型。样本值已被规范化,每个样本均通过模糊偏秩模型进行排名。建立连续值的决策信息列表,以解决一般粗糙集中必须存在决策信息列表的问题。然后,根据属性的一般重要性计算每个属性值的权重系数,从而避免通过分散对噪声敏感的属性值来避免不良的后效应,并克服了一般粗糙集难以在连续属性中使用的问题。 -可比性,变化范围和强烈的对抗性。然后通过模糊偏序和粗糙集方法验证了整个员工绩效管理后评价的可行性和有效性。

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