School Choice Of Auxiliary Information System For Rural Areas

Every year colleges select their students according to the National collegeentrance exam. The examination is an important turning point for every student’sfuture. This examination not only contains hope of family but also has great effect onthe social talented persons’ training plan. The most important thing in college entranceexamination process is the application. Especially for rural areas candidates, many ofthem living in remote mountainous areas lack of information, they don’t know whichcollege they want to go, and they could not realize the examination scores is thepremise for the application. Unfortunately, many students whose scores can’t reachthe admission scores fall the examination. It is a fatal blow to more than ten yearslearning rural students. According to these, it is a great significance to construct anintelligence system which could provide school choice support to rural students’applications. This system could integrate different factors together which have greateffect on rural students’ applications, and show the recommendations to users. Thispaper mainly does the following researches:1. Analyzed the main factors that have great influence on rural students’applications: the resources of teachers, the conditions of colleges, the employmentrates, and sustainable development. Based on students’ scores, we integrate thesefactors together to build are commend application model.2. Improved artificial fish swarm algorithm. Standard artificial fish swarmalgorithm run a slow speed at end, in order to improve the speed, the current optimalsubgroup center position is added to the bulletin board; and improved the behavior ofprey, swarm, and follow, so as to enhance the speed of algorithm and reduce theiterative time.3. Improved Fuzzy c-means clustering algorithm. We have amount ofinstitutions data information, and the recommendation results required high reliability,but the selection of initial cluster center have great effect on fuzzy c-means clusteringalgorithm results. This paper combined the improved artificial fish swarm algorithmwith fuzzy c-means algorithm. Avoiding the two algorithms’ weaknesses, theselection of initial cluster center is provided by the improved artificial fish swarmalgorithm, which makes the fuzzy c-mean algorithm enhance efficiency.4. By using Analytic Hierarchy Process (AHP)to sort the clustering results. According to the examinee values the factors that have great effects on school choice,we construct the structure model of school choice system. With the help of this model,we can sort the clustering results. The results could give the examinee a clearlyscientific sequence of how to choose colleges.5. Build school choice of auxiliary information system for rural areas.Thissystem is developed in Netbeans by using JAVA、 JSP、 SQL Server2005. Firstly,students enter their scores and select batch, system will display the college list thatstudents’ score could reach the college admission lines; secondly, among the list,students set values to each factors; thirdly, with the help of new algorithm thatcombined AFAS with FCM, we get the college clustering results, in order tocorrespond students’ requirement, the system use AHP to get the sort of clusteringresults. This system can give candidates scientific advice of school choice.