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

机译:基于模糊部分排序和粗糙集的全人员绩效管理的后评估方法

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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:为了解决整个员工绩效管理的每个属性的权重的问题通常是主观的多属性评估,基于模糊部分排序和粗糙集理论的整个员工性能管理评估模型。样本值已归一化,每个样品由模糊部分等级模型排列。建立了连续值的决策信息列表,以解决一般粗糙集中必须有决策信息列表的问题。然后基于属性的广义重要性来计算每个属性值的权重系值,以避免通过将噪声敏感的属性值分散并克服常规粗糙集在连续属性中难以使用的问题来处理的不良后遗症,这与噪声难以使用 - 组织性,变异范围和强拮抗作用。然后,通过模糊部分排序和粗糙集方法验证了整个员工绩效管理后评估的可行性和有效性。

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