Show simple item record

dc.contributor.authorNakip, M.
dc.contributor.authorGul, B.C.
dc.contributor.authorRodoplu, V.
dc.contributor.authorGuzelis, C.
dc.date.accessioned2021-01-25T20:48:12Z
dc.date.available2021-01-25T20:48:12Z
dc.date.issued2019
dc.identifier10.1145/3361821.3361833
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85076754111&doi=10.1145%2f3361821.3361833&partnerID=40&md5=9395d0249c6d34d8f052a476abb6cf81
dc.identifier.urihttps://dspace.yasar.edu.tr/xmlui/handle/20.500.12742/9800
dc.description.abstractWe 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
dc.language.isoEnglish
dc.publisherACM International Conference Proceeding Series
dc.titleComparative study of forecasting schemes for IoT device traffic in machine-to-machine communication
dc.typeConference Paper
dc.relation.firstpage102
dc.relation.lastpage109
dc.description.affiliationsYaşar University, P.O. 35100, Bornova Izmir, Turkey


Files in this item

FilesSizeFormatView

There are no files associated with this item.

This item appears in the following Collection(s)

Show simple item record