首页|大规模创新类竞赛评审方案研究

大规模创新类竞赛评审方案研究

扫码查看
基于某大规模创新类竞赛的相关模拟评审数据,首先,通过讨论两评审阶段成绩与极差的变化,分析现有评审方案各自的优劣;其次,构建极差模型,运用Adaboost算法检验模型的预测效果;最后,针对现有评审方案的不足,对未来评审方案改革提出展望.研究结果表明:两阶段评审和不分阶段评审各有优劣,极差模型预测效果较好.
Research on Evaluation Scheme of Large-scale Innovation Competition
Based on the relevant simulation review data of a large-scale innovation competi-tion,firstly,the advantages and disadvantages of the existing review schemes are analyzed by discuss-ing the changes of the results and ranges in the two review stages.Secondly,the range model is con-structed and the Adaboost algorithm is used to test the prediction effect of the model.Finally,in view of the shortcomings of the existing evaluation schemes,the future evaluation scheme reform is pro-posed.The results show that both two-stage review and non-stage review have their own advantages and disadvantages,and the range model has better prediction effect.

large-scale innovation competitionevaluation schemeAdaboost algorithmrange model

陈齐萌

展开 >

安徽理工大学经济与管理学院,安徽淮南 232000

大规模创新类竞赛 评审方案 Adaboost算法 极差模型

2024

太原师范学院学报(自然科学版)
太原师范学院

太原师范学院学报(自然科学版)

影响因子:0.127
ISSN:1672-2027
年,卷(期):2024.23(2)