Prediction of user throughput in the mobile network along the motorway and trunk road
Journal Title: SCIENCE, ENGINEERING AND TECHNOLOGY - Year 2022, Vol 2, Issue 2
Abstract
The main goal of this research is to create a machine learning model for predicting user throughput in the mobile 4G network of the network provider M:tel Banja Luka, Bosnia and Herzegovina. The geographical area of the research is limited to the section of Motorway "9th January" (M9J) Banja Luka - Doboj, between the node Johovac and the town of Prnjavor (P-J section), and the area of the section of trunk road M17, between the node Johovac and the town of Doboj (J-D section). Based on the set of collected data, several models based on machine learning techniques were trained and tested together with the application of the Correlation-based Feature Selection (CFS) method to reduce the space of input variables. The test results showed that the models based on k-Nearest Neighbors (k-NN) have the lowest relative prediction error, for both sections, while the model created for the trunk road section has significantly better performance.
Authors and Affiliations
Zoran Ćurguz, Milorad Banjanin, Mirko Stojčić
Keywords
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- EP ID EP710346
- DOI https://doi.org/10.54327/set2022/v2.i2.38
- Views 46
- Downloads 0
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