A Study of Judging Scheme for Innovative Category Competitions Based on Stochastic Simulation and T-Score Methods

Abstract

This study proposes a set of fair and accurate judging optimization scheme for the judging problem in science and technology innovation competitions. First, by simulating random distribution, a work allocation model is designed to achieve balanced judging workload and minimize work intersection. Second, the T-score method is introduced to optimize the calculation of standard scores in order to reduce the subjectivity and polarity of scoring. Again, a segmentation management strategy is proposed to effectively screen and highlight innovative works by setting score thresholds and dividing works into different grades. This scheme improves the scientificity and fairness of evaluation through reasonable allocation, scoring standardization and segmented screening, which is of guiding significance to the evaluation of science and technology competitions.