{"title":"Research on Intelligent Scheduling Optimization Selection Algorithm for Medical Information","authors":"Ming Li, R. Hu, Hong Xu, Huimin Zhao, Xueri Li","doi":"10.2991/ICMEIT-19.2019.74","DOIUrl":null,"url":null,"abstract":"Aiming at the problems of asymmetric information and long delay time and excessive use of network traffic and inaccurate recommendation in the traditional medical information recommendation algorithm, the improved adaptive scheduling algorithm and intelligent optimization recommendation algorithm are combined, it can completely solve the problems of time, traffic occupancy, stability and accuracy of medical information push. In this paper, an improved adaptive scheduling algorithm is proposed to solve the problems of time occupancy, traffic flow and connection stability of medical information recommendation. The proposed intelligent optimization recommendation algorithm solves the accuracy problem of medical information recommendation. Experimental results show that the proposed algorithm has the advantages of short delay time, low flow occupation, stable connection and high accuracy of push.","PeriodicalId":223458,"journal":{"name":"Proceedings of the 3rd International Conference on Mechatronics Engineering and Information Technology (ICMEIT 2019)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 3rd International Conference on Mechatronics Engineering and Information Technology (ICMEIT 2019)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2991/ICMEIT-19.2019.74","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Aiming at the problems of asymmetric information and long delay time and excessive use of network traffic and inaccurate recommendation in the traditional medical information recommendation algorithm, the improved adaptive scheduling algorithm and intelligent optimization recommendation algorithm are combined, it can completely solve the problems of time, traffic occupancy, stability and accuracy of medical information push. In this paper, an improved adaptive scheduling algorithm is proposed to solve the problems of time occupancy, traffic flow and connection stability of medical information recommendation. The proposed intelligent optimization recommendation algorithm solves the accuracy problem of medical information recommendation. Experimental results show that the proposed algorithm has the advantages of short delay time, low flow occupation, stable connection and high accuracy of push.