Abstract
One of the features of the mobile data network operators is the need for continuous monitoring and maintenance of equipment and communication channels. The equipment failures that sometimes occur increase the cost of operation and reduce customer loyalty. The ability to predict network malfunctions in advance would be a great solution for mobile operators. The paper discusses the issue of preliminary data preparation of 4G+ mobile network for further use in the development of a neural network model for predicting malfunctions. The results of the analysis of the collected data are presented, the characteristics, composition and data structure that may affect the training of the neural network model later are shown.
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