Campus Network User Demand Forecasting Model Based on Multiple Linear Regression
- https://doi.org/10.2991/icesem-18.2018.212How to use a DOI?
- Campus network; User demand; Least squares method; Ridge regression
By analyzing the relationship between campus network users and online processes, a campus network user demand forecasting model based on multiple linear regression is proposed. Firstly, influencing factors are analyzed through scatter plots and trend lines, and the main factors affecting the Internet access needs of campus users are selected, namely, service reachability, service response time, service interruption rate, service quality, and service ease of use. Secondly, the statistical software SPSS 22 is used to construct a multiple linear regression model based on least squares method, and the multi-collinearity problem between independent variables is eliminated by ridge regression analysis to obtain modified model. Finally, the model is used to meet the needs of campus users. The prediction is carried out, and the result shows that the accuracy of the predicted estimation value is high, indicating that the model has good fitting degree and has certain practicability and reference significance.
- © 2018, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Xuefeng Li PY - 2018/08 DA - 2018/08 TI - Campus Network User Demand Forecasting Model Based on Multiple Linear Regression BT - Proceedings of the 2018 2nd International Conference on Education Science and Economic Management (ICESEM 2018) PB - Atlantis Press SP - 908 EP - 911 SN - 2352-5398 UR - https://doi.org/10.2991/icesem-18.2018.212 DO - https://doi.org/10.2991/icesem-18.2018.212 ID - Li2018/08 ER -