学术论文评审的同行评议专家共识问题研究

Research on Consensus Problem of Peer Review in the Evaluation of Academic Papers

根据多属性群决策原则,本文提出了一种提高学术论文同行评议的共识度方法——同行专家相互评判的评审方法。即在每位同行评议专家单独评审的基础上,由编辑部将每位同行评议的评审意见和结果反馈到其他同行评议专家的手中,并进行相互逆判,以此得到同行评议专家的群体认可度(据此,可以计算专家权重)。本文将同行评议专家的评判偏好以区间数形式表示,并将其映射成二维坐标平面上的点集,通过引入Weber点对同行评议专家的评判偏好点进行加权集结。本文采用模拟植物生长算法(PGSA),求取集结点,并将其作为评判的依据。最后,本文通过学术论文评审的实例分析以及与其他方法精度比较,说明了该方法的有效性和可行性。

According to the principle of multiple attribute group decision making, the paper proposes a method, that is reciprocal judgment by peer experts to improve the consensus of peer review of academic papers in the article. On the basis of a separate review by each peer review expert, the editorial department will feed back each expert＇s comments and results to other peer review experts and conduct mutual judgment. By this way, group consensus degree of each peer expert （accordingly, expert weights can be calculated） is gained. In this paper, the judgment preferences of peer experts are expressed in the form of interval number and mapped into two-dimensional coordinate plane. By introducing the Weber point, the judgment preferences of peer experts are aggregated. In this paper, the Plant Growth Simulation Algorithm （PGSA）is used to obtain the aggregation point. And the aggregation point is used as the basis for evaluation. Finally, this paper illustrates the effectiveness and feasibility of the method by giving an example of academic paper review and comparing with other method.