Construction Analysis of Peer-Reviewed Evaluation Model Based on Inverse Cloud Algorithm
Peer review is still essentially a quantitative subjective qualitative review,the cornerstone of which is to participate in the review activities of each reviewer,only to do an effective assessment of the reviewer,supervision,standardization,and constraints,in order to ensure that the results of the peer review of the objectivity and fairness.However,the peer review process is always uncertain,how to deal with uncertainty is a difficult problem to be solved by peer review.For this reason,on the basis of discussing the necessity of reviewer evaluation in peer review and the current development overview,the evaluation data of peer review is used to analyze the reviewers and the factors influencing the review,and a scientific peer review evaluation model is constructed based on the data.Using cloud model theory,for the characteristics of peer review,this paper selects the inverse cloud generation algorithm that conforms to the statistical nature of normal distribution and uncertainty,decomposes the program into 2 levels of reviewer review evaluation and multi-task collaborative review evaluation,and puts forward the peer review evaluation model.Further,the paper utilizes the peer review of a certain type of talent project of a certain province in China for the period of 2018-2022 in 6 directions of technology,foresight,output,risk,economy and society with a total of 18 review indicators,through the model classification and hierarchy to calculate its cloud model digital features,according to the digital features to build cloud diagrams and digital portraits for analysis.The results show that:the peer review evaluation model based on the reverse cloud algorithm has practical significance for evaluating the reviewer's ability in all aspects of the review and the overall effect of the review,evaluating the effectiveness of the peer review activities,and supervising the abnormal data in the peer review.It can scientifically build the personalized authority of the reviewer,give full play to the maximum advantage of the reviewer,minimize the error caused by human factors,and alleviate the current peer review evaluation.It can also minimize the errors caused by human factors and alleviate the current predicament of peer review evaluation.
peer reviewevaluation modelmodel buildinginverse cloud algorithmcloud modeldigital features
NETL
NSTL
万方数据
