Team Formation For Discipline Competition Based On Entropy Weighted Clustering

Nowadays,foreign countries are imposing various blockades on China in terms of core technologies.China needs to rely on its own capabilities to break through obstacles.The "14th Five-Year Plan" also mentions the importance of scientific and technological innovation.Innovation promotes the progress of science and technology,and subject competition is an important way to cultivate students’ innovative ability.Participating in subject competition is conducive to stimulating students’ innovative vitality and optimizing the school’s innovation ecology.Nowadays,people’s production and lifestyle have gradually shifted from offline to online,and people have gradually become accustomed to being able to complete the work they need to do online.Therefore,the team formation in the subject competition in this thesis aims to create a platform to help students participate in the competition and help schools manage the competition,so as to ensure the maximum benefit of participating in the competition.This thesis mainly studies the team formation algorithm of subject competition based on entropy weighted clustering and its application.First of all,it analyzes the research status of subject competitions,and understands the different practices of others;then,it studies the existing management system of subject competitions,analyzes the organization process and participation process of subject competitions,and takes mathematical modeling competition as an example to conduct data analysis,to provide a theoretical basis for establishing a discipline team model and designing a discipline competition management system;by studying the entropy weight method,ID3 decision tree and clustering,and applying them to the team formation algorithm,the student selection,team formation and learning resource group The recommendation is integrated into one,and together constitute the team function module of the discipline competition management system;then based on the MVC architecture,the demand analysis and design of the discipline competition management system are carried out,and the functional modules of the system are analyzed in detail.The team algorithm was applied to the system;finally,the research and development of the discipline competition management system was completed through continuous testing and adjustment.In terms of team matching,this thesis uses the ID3 decision tree algorithm to screen the participating players,and then selects the preference of the members who pass the screening to complete the team recommendation.In terms of group recommendation of learning resources,in order to improve the level of competition by using the time before the competition,this article recommends competition resources for the teams that have been formed and in groups,in line with the learning habits of the group,thereby improving the learning efficiency of the group.The ultimate goal of this project is to carry out pre-competition training in groups through reasonable pairings,so as to improve the competition level of the contestants,so as to ensure the best competition benefits.On the basis of the analysis of the discipline competition management system,the analysis of the discipline competition process and the research on the team formation algorithm,the research and development of the discipline competition management system has been successfully completed,and the team formation algorithm has also been successfully applied to the system.were successfully implemented.