“双一流”背景下ESI潜力学科识别与入围预测模型构建的实践探索--以福建医科大学为例

Practice of Identification and Prediction of ESI-covered Potential Disciplines under the Background of“Double First-class”Initiative——Taking Fujian Medical University as an Example

预测高校优势潜力学科及其入围ESI全球前1%的时间,既是“双一流”学科建设中科学制定发展规划的依据,也是高校图书馆学科服务中的重要组成部分。文章采用潜力值区间划分和SWOT分析两种方法对优势潜力学科进行识别,并以科研人员样本数据获取时效性为区分点,结合非线性回归算法和时间序列分析法,构建了曲线拟合实时预测模型与双指标回溯预测模型。并以福建医科大学化学学科为例进行实证研究。结果显示潜力学科区间划分与SWOT分析存在较高统一性,实时预测模型与回溯预测模型拟合结果高度一致,预测结果可信度高,证明模型构建具备科学性和实用性。

To identify the potential key disciplines and estimate the time for these disciplines to rank top 1%in the ESI index,is not only the basis of making a reasonable plan in the construction of“Double First-class University Plan”key disciplines,but also an indispensable part of the service of university libraries.This paper adopts two methods in the identification of potential key disciplines,namely,the potential value interval division and the SWOT analysis.Taking the timeliness of sample data as division points,combined with nonlinear regression algorithm and time series analysis,the curve fitting real-time prediction model and the two-indicator backtracking prediction model are constructed.Based on the chemistry discipline of Fujian Medical University,we conduct a quantitative research.As a result,the potential key subject division results and the SWOT analysis results are highly consistent.The goodness of fit of the real-time prediction model and the backtracking prediction model are similar.In conclusion,the prediction is highly reliable,and the model is proved to be both scientific and practical.