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Research on Intelligent Correction of Abnormal Data in Online Education System Based on Big Data Technology

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e-Learning, e-Education, and Online Training (eLEOT 2021)

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Abstract

In the traditional correction method of abnormal data in online education system, the unreasonable selection of training samples by RBF neural network leads to a large error in the correction of abnormal data. Therefore, GA algorithm is used to improve RBF neural network, and a new intelligent correction method of abnormal data in online education system based on big data technology is proposed. The classification model of abnormal data in online education system is constructed by decision tree classification algorithm. The pretreatment of abnormal data is completed based on big data technology. The specific pre-processing steps include: data cleaning, data integration, data transformation, data reduction, dimension reduction, numerical reduction, data discretization and concept layering. GA-RBF neural network is used to correct abnormal data of online education system. By comparing the performance of this method with the traditional intelligent correction method of abnormal data in online education system, it can be seen that the prediction and filling accuracy of this method is higher than that of the traditional method, and the performance is improved.

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Authors and Affiliations

  1. South China Institute of Software Engineering GU, Guangzhou, 510990, China

    Yana Tang

  2. Xi’an International Studies University, Xi’an, 710128, China

    Jing Zhao

Authors
  1. Yana Tang
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  2. Jing Zhao
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Editor information

Editors and Affiliations

  1. Hunan Normal University, Changsha, China

    Weina Fu

  2. Hunan Normal University, Changsha, China

    Shuai Liu

  3. Hunan Normal University, Changsha, China

    Jianhua Dai

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© 2021 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Tang, Y., Zhao, J. (2021). Research on Intelligent Correction of Abnormal Data in Online Education System Based on Big Data Technology. In: Fu, W., Liu, S., Dai, J. (eds) e-Learning, e-Education, and Online Training. eLEOT 2021. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 390. Springer, Cham. https://doi.org/10.1007/978-3-030-84386-1_38

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  • DOI: https://doi.org/10.1007/978-3-030-84386-1_38

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-84385-4

  • Online ISBN: 978-3-030-84386-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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