Abstract
Online preschool education decision support system has the problem that large-scale data can not be calculated in parallel, which affects the efficiency of random data writing and reading. An online preschool education decision support system based on data mining is designed. In the hardware part, CS5368 chip is used to realize the storage function of the acquisition node, 64K static random access memory 23LCV512 is used as the buffer, and SRAM reads and writes in byte mode. In the software part, the overall system is based on B/S architecture and combined with web technology to make the whole system application run on the server side. Using data mining technology to establish a database, the decision-making process of online preschool education is regarded as a classification and prediction problem. Design the system function module to complete the management operations such as data addition, deletion, modification and query. The system performance test results show that the total time and rate of random data writing and reading of the system are obviously better than the decision support system based on GA-BP neural network and artificial intelligence, so it has higher data processing efficiency and load capacity.
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© 2022 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Li, N., Li, M. (2022). Design of Online Preschool Education Decision Support System Based on Data Mining. In: Fu, W., Sun, G. (eds) e-Learning, e-Education, and Online Training. eLEOT 2022. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 453. Springer, Cham. https://doi.org/10.1007/978-3-031-21161-4_15
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DOI: https://doi.org/10.1007/978-3-031-21161-4_15
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