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机构地区:[1]上海理工大学机械工程学院,上海
出 处:《建模与仿真》2024年第2期1311-1321,共11页Modeling and Simulation
摘 要:近年来,大规模创新比赛越来越多,参赛人数和参赛作品的数量也越来越多,这就要求我们建立更加公平合理科学的大赛评审方案。现阶段这类比赛一般采用两阶段(网评、现场评审)或三阶段(网评、现场评审和答辩)评审,然而当竞赛规模巨大并且评委评分出现较大分歧时,现有的评审机制不能够较好地解决这类问题。为了提高大赛评分的科学性与客观性,本文首先建立线性规划模型将现有的专家集和作品集以交集最大化进行分类完成准备工作,其次对现有的评分标准进行改进引入总体均值和方差完成对初始标准分模型的优化,最后建立极差模型对评分结果中“极差”较大的作品进行分类判断其是否需要下一阶段的复议。In recent years, there have been more and more large-scale innovation competitions, and the num-ber of participants and entries has also increased, which requires us to establish a more fair, rea-sonable and scientific evaluation scheme for the competition. At this stage, this kind of competition generally adopts two stages (online evaluation, on-site evaluation) or three stages (online evalua-tion, on-site evaluation and defense) evaluation, but when the scale of the competition is huge and the judges’ scores are quite different, the existing evaluation mechanism can not solve this kind of problem well. In order to improve the scientificity and objectivity of the scoring of the competition, this paper firstly establishes a linear programming model, classifies the existing expert set and the portfolio to maximize the intersection to complete the preparatory work, then improves the exist-ing scoring criteria, introduces the population mean and variance, and completes the optimization of the initial standard score model, and finally establishes a range model to classify the works with large “range” in the scoring results to determine whether they need the next stage of reconsidera-tion.
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