基于决策树模型的智能导检排队算法及应用效果
Intelligent Guided Examination and Queuing Algorithm Based on Decision Tree Model and its Application Effect
王晓华1
作者信息
摘要
目的 通过智能算法降低体检排队时长,优化体检流程,提高体检效率.方法 采用决策树算法,考虑影响体检排队的各因素,通过计算得出最优体检路径,为体检者合理安排体检流程,减少其等候和排队时间.结果 智能导检实施后的体检中位时长平均值比实施前少16分钟(P=0.002 3),说明体检用时明显减少,中位时长的波动区间比实施前少13到16分钟,说明波动区间也减少.结论 智能导检能够降低体检者盲目性,减少体检时长,提高体检效率.
Abstract
Objective Intelligent algorithms are used to reduce physical examination queue time,optimize the physical examination process and improve physical examination efficiency.Methods Using decision tree algorithm,the optimal physical examination path is calculated for considering various factors that affect the queuing of physical examinations,in order to reasonably arrange the physical examination process for examinees and reduce their waiting and queuing time.Results From the data comparison before and after the implementation of intelligent guided examination,the physical examination median average duration after implementation is 16 minutes(P=0.0023)less than that before implementation,indicating that the time for physical examination is significantly reduced,and the fluctuation range of median duration is 13 to 16 minutes less than that before implementation,indicating that the fluctuation range is also reduced.Conclusion Intelligent guided examination can reduce the blindness of physical examination personnel,reduce the average duration of physical examination,and improve the efficiency of physical examination.
关键词
算法/决策树/体检管理/智能导检Key words
algorithm/decision tree/physical examination management/intelligent guided examination引用本文复制引用
出版年
2024
NETL
NSTL
万方数据