dc.contributor.author | Nakip, M. | |
dc.contributor.author | Gul, B.C. | |
dc.contributor.author | Rodoplu, V. | |
dc.contributor.author | Guzelis, C. | |
dc.date.accessioned | 2021-01-25T20:48:12Z | |
dc.date.available | 2021-01-25T20:48:12Z | |
dc.date.issued | 2019 | |
dc.identifier | 10.1145/3361821.3361833 | |
dc.identifier.uri | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85076754111&doi=10.1145%2f3361821.3361833&partnerID=40&md5=9395d0249c6d34d8f052a476abb6cf81 | |
dc.identifier.uri | https://dspace.yasar.edu.tr/xmlui/handle/20.500.12742/9800 | |
dc.description.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 | |
dc.language.iso | English | |
dc.publisher | ACM International Conference Proceeding Series | |
dc.title | Comparative study of forecasting schemes for IoT device traffic in machine-to-machine communication | |
dc.type | Conference Paper | |
dc.relation.firstpage | 102 | |
dc.relation.lastpage | 109 | |
dc.description.affiliations | Yaşar University, P.O. 35100, Bornova Izmir, Turkey | |