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传统的科技奖励评价方法主观性较强,会造成信息失真,利用未确知测度模型能有效地解决这种主观性问题。在借鉴未确知测度模型的基础上,运用概率向量和等级空间向量的运算对其评价准则进行改进,构建了一个含有综合得分公式的未确知测度评分模型。通过实证研究可以看出,未确知测度评分模型比传统的科技奖励评价模型更能减少由专家主观性所产生的信息失真,使得评价结果更客观、公平、科学、直观,具有较强的可操作性和实用性。
The traditional method of reward evaluation of science and technology is subjective and will result in information distortion. Using the unascertained measure model can effectively solve this subjectivity problem. Based on the model of unascertained measure, this paper improves the evaluation criterion by using the operation of probability vector and level space vector, and constructs a score model of unascertained measure with integrated score formula. Through the empirical study, we can see that the unascertained measure scoring model can reduce the information distortion caused by the subjectivity of experts more than the traditional sci-tech evaluation models, making the evaluation results more objective, fair, scientific and intuitive and strong Operability and practicality.