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Anomaly detection in a mobile data network
The dissertation investigated the creation of an anomaly detection approach to identify anomalies in the SGW elements of a LTE network. Unsupervised techniques were compared and used to identify and remove anomalies in the training data set. This “cleaned” data set was then used to train an autoe...
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| Format: | Thesis |
| Language: | English |
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Department of Statistical Sciences
2020
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