贪心算法在智能导检中的应用研究

Research on the Application of Greedy Algorithm in Intelligent Guidance of Health Examination

基于贪心算法建立可靠的智能导检路径优化模型,依据预测多个检查项目的体检顺序及时间节点信息,优化健康体检时间。将2021年3月份江苏省中医院体检中心的体检数据作为初始数据样本,经过数据清洗最终选择29126条数据作为研究对象,利用最小二乘法拟合数据构建体检客户到达率与时间的函数关系,将误差平方和(SSE)及R-square作为评价指标,建立以服务时间、排队时间、路程时间三者总时间的智能导检模型。研究结果表明,体检客户到达率SSE值分别为5.115、0.7878、4.541等,R-square值分别为0.9796、0.9967、0.8986等。模型拟合效果较好,基于贪心算法的智能导检模型完成规划体检顺序,预测体检路径。

A reliable intelligent guided physical examination path optimization model was established based on greedy algorithm,and the physical examination time was optimized according to the physical examination sequence and time node information of multiple ex⁃amination items.The physical examination data of physical examination center of Jiangsu Hospital of Traditional Chinese Medicine in March 2021 were taken as the initial data samples,and 29126 data were selected as the research objects after data cleaning,and the least square method was used to fit the data to construct the functional relationship between the physical examination client arrival rate and time.The sum of squares of error(SSE)and R-Square were used as evaluation indexes.An intelligent guided physical examination model was established based on the sum of service time,queuing time and walking time.the research results show that the error sum of squares(SSE)of physical examination customer arrival rate were 5.115,0.7878,4.541,etc.,and the R-Square values were 0.9796,0.9967,0.8986,etc.,respectively.The fitting effect of the test model was significant.The intelligent guided physical examination mod⁃el based on greedy algorithm can complete the planning of physical examination sequence and predict the physical examination path.