摘要
针对科技奖励评价中各指标权重的不确定性问题,提出随机森林赋权法,利用可靠性分析计算专家评分数据的泛化误差,根据最小错误率得到各评价项目的各评价指标权重,减少主观赋权的影响;引入一致可信度、非一致可信度和净可信度信息,提出改进的ELECTRE-Ⅲ方法,将某一评价项目优于其他评价项目的程度具体量化,解决专家评分数据为次序变量的问题.实证表明:随机森林赋权法和改进后的ELECTRE-Ⅲ方法相结合,既提高了权重估计的精确度和可信度,又解决了难以给定门槛值和不能完全排序的问题,使评价结果更加科学、客观、合理.
To address the uncertainty of the target weight in assessing science and technology awards,the Random Forest Weighting Method was proposed.Reliability analysis was used to calculate the generalization error of expert evaluation data,and according to the minimum error rate,to obtain the evaluation project of each evaluation index weight and to reduce the impact of subjective weighting.Consistently reliable information,inconsistently reliable information and net reliable information were introduced.An improved ELECTRE-Ⅲ method was put forward to solve the problem of expert evaluation data for order variability.A specific number to measure a certain degree of an evaluation project is superior to other evaluation project.Empirical evidence shows that the combination of the Random Forest Weighting Method with the improved ELECTRE-Ⅲ method not only improve the accuracy and reliability of weight estimation,but also solve the problem of inability to set threshold level and rank completely,leading to more scientific,objective and reasonable evaluation results.
出处
《湖南大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2015年第3期140-144,共5页
Journal of Hunan University:Natural Sciences
基金
国家自然科学基金资助项目(71340003)
国家社会科学基金资助项目(14BTJ003)~~
