Predicting Overall Budget Performance Evaluation of Research Institutions
[Objective]This paper aims to ensure the objectivity,timeliness,and accuracy of the overall budget performance evaluation of research institutions,and to improve the efficiency of performance evaluation work.[Methods]We proposed a method for predicting research institutions'overall budget performance evaluation based on LightGBM.Our method integrates various data from scientific research management information systems.It uses machine learning algorithms to analyze and predict the overall budget performance evaluation results by correlating research inputs and outputs with performance.[Results]In the application of the overall budget performance evaluation of research institutions,the accuracy of the proposed method reached 94.12％.The human resources required for the budget performance evaluation process were reduced from 10 people to 5,and the time cost was shortened from 38 days to about 10 days.[Limitations]Some performance evaluation indicators are subjective and difficult to quantify using business data from scientific research management information systems.[Conclusions]The proposed method has excellent performance in predicting overall budget performance evaluation results.It reduces the fairness issues due to subjective evaluation,and saves the human resources and time costs in budget performance evaluation,thus improving their efficiency.
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