基于逆向云算法的同行评议评价模型初建[*]

Peer review evaluation based on inverse cloud algorithm

摘要:

同行评议是一种基于科学共同体的群体决策行为，受各种因素影响，难以用精准的、定量形式给出准确信息，本质上依然是一种量化过的主观定性评议，评议者评议质量关系着同行评议结论的科学性、公平性与公正性。首先，本文基于逆向云算法进行同行评议评价方法研究，提出同行评议评价模型；其次，利用逆向云算法从杂乱的数据中，分类分层次计算出数字特征，并根据数字特征构建云图和数字画像进行分析。本文通过梳理同行评议评价的发展脉络、研究趋势与应用现状，验证提出的评价方案，结果表明本文的算法提高并完善了评价同行评议活动的功能，具有一定的应用价值。

Abstract:

Peer review is a group decision-making behavior based on the scientific community, which is influenced by various factors and difficult to provide accurate information in a precise and quantitative form. Essentially, it is still a quantitative subjective qualitative review, and the quality of peer review is related to the scientificity, fairness, and impartiality of peer review conclusions. Firstly, this paper studies peer review evaluation method based on reverse cloud algorithm, and puts forward peer review evaluation model. Secondly, the reverse cloud algorithm is used to classify and stratify the digital features from cluttered data, and build cloud maps and digital portraits according to the digital features for analysis. This paper reviews the development, research trends, and application status of peer review and evaluation, and verifies the proposed evaluation scheme. The results show that the proposed algorithm improves the function of evaluating peer review activities to some extent, and has certain practical value.