Comparative study of forecasting schemes for IoT device traffic in machine-to-machine communication
Abstract
We present a comparative study of Autoregressive Integrated Moving Average (ARIMA), Multi-Layer Perceptron (MLP), 1-Dimensional Convolutional Neural Network (1-D CNN), and Long-Short Term Memory (LSTM) models on the problem of forecasting the traffic gene
URI
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85076754111&doi=10.1145%2f3361821.3361833&partnerID=40&md5=9395d0249c6d34d8f052a476abb6cf81https://dspace.yasar.edu.tr/xmlui/handle/20.500.12742/9800
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