Analysis On The Use Of Science And Technology Museum Exhibition Based On K - Means Clustering Algorithm

With the progress of China’s continuous economic, science technology development, and the strategy of Sustainable development, the strategy of invigorating the country through science, the implementation of the national scientific literacy program are paid much attention. In order to develop people’s scientific cultural quality and cultivation, lots of science museums are constructed.In this social context, Yunnan Science and Technology Museum is under construction. After investigation and observation we found that there exist some problems, such as many exhibits on display.Thus, the visitors can not finish all of them in a daytime. They have no time to try and get to know the exhibits, which causes resource waste. In order to avoid this kind of problem, we are not only upgraded the quality of our exhibits, but also improved the routes of our exhibits. Only by this way, we can apply a better-personalized service, which can make them learn more from the exhibitions. Moreover, we should analyze the hobbies of the visitors, visitors’ acceptable degree. The main contents of this thesis are as follow:1. The basic study on exhibits and visitors’ data collectingAccording to the usage of the RFID, combined with the classification and the display of exhibits, this thesis focuses on the study of the relationship between exhibits and visitors.2. We analyse the relationship between exhibits and visitors based on the K-means clustering.Depended on the characters of highly mobile and flexible visitors, this thesis use the K-means clustering to do the data analysis and makes the conclusion which are very important to the museum’s future development.