{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,16]],"date-time":"2026-07-16T21:19:04Z","timestamp":1784236744973,"version":"3.55.0"},"reference-count":43,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2022]]},"DOI":"10.1109\/access.2022.3221970","type":"journal-article","created":{"date-parts":[[2022,11,14]],"date-time":"2022-11-14T21:42:06Z","timestamp":1668462126000},"page":"119607-119616","source":"Crossref","is-referenced-by-count":44,"title":["Fed-NTP: A Federated Learning Algorithm for Network Traffic Prediction in VANET"],"prefix":"10.1109","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9914-1767","authenticated-orcid":false,"given":"Sanaz Shaker","family":"Sepasgozar","sequence":"first","affiliation":[{"name":"Department of Computer and Software Engineering, Mobile Computing and Networking Research Laboratory (LARIM), Polytechnique Montreal, Montreal, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Samuel","family":"Pierre","sequence":"additional","affiliation":[{"name":"Department of Computer and Software Engineering, Mobile Computing and Networking Research Laboratory (LARIM), Polytechnique Montreal, Montreal, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref39","author":"g\u00e9ron","year":"2019","journal-title":"Hands-On Machine Learning with Scikit-Learn Keras and TensorFlow Concepts Tools and Techniques to Build Intelligent Systems"},{"key":"ref38","article-title":"A generic framework for privacy preserving deep learning","author":"ryffel","year":"2018","journal-title":"arXiv 1811 04017"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.3390\/s22124394"},{"key":"ref32","first-page":"139","article-title":"Overview of long short-term memory neural networks","author":"smagulova","year":"2019","journal-title":"Deep Learning Classifiers With Memristive Networks"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1016\/j.comnet.2021.108102"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2022.3144112"},{"key":"ref37","first-page":"1","article-title":"PyTorch: An imperative style, high-performance deep learning library","volume":"32","author":"paszke","year":"2019","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref36","author":"van rossum","year":"1995","journal-title":"Python 3 Reference Manual CreateSpace"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1145\/1080754.1080769"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.3390\/electronics11040573"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/ICITE.2019.8880220"},{"key":"ref40","year":"2022","journal-title":"Google colab"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.5753\/courb.2020.12361"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.2968399"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1016\/j.future.2020.12.003"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1016\/j.comnet.2022.108906"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2021.3055283"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/INFOCOM42981.2021.9488883"},{"key":"ref17","author":"italia","year":"2015","journal-title":"Telecommunications&#x2014;SMS call internet&#x2014;TN"},{"key":"ref18","author":"italia","year":"2015","journal-title":"Telecommunications&#x2014;SMS Call Internet&#x2014;MI"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/ICC.2006.254860"},{"key":"ref4","first-page":"374","article-title":"Towards federated learning at scale: System design","volume":"1","author":"bonawitz","year":"2019","journal-title":"Proc Mach Learn Syst"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2022.3157056"},{"key":"ref3","first-page":"2342","article-title":"An empirical exploration of recurrent network architectures","author":"jozefowicz","year":"2015","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1016\/j.renene.2003.11.009"},{"key":"ref6","article-title":"Federated optimization: Distributed machine learning for on-device intelligence","author":"kone?n\u00fd","year":"2016","journal-title":"arXiv 1610 02527"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/INFOCOMWKSHPS54753.2022.9798018"},{"key":"ref5","first-page":"1273","article-title":"Communication-efficient learning of deep networks from decentralized data","author":"mcmahan","year":"2017","journal-title":"Proc Artif Intell Statist"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/MSP.2020.2975749"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.3233\/IA-200075"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2016.2582924"},{"key":"ref1","article-title":"Empirical evaluation of gated recurrent neural networks on sequence modeling","author":"chung","year":"2014","journal-title":"arXiv 1412 3555"},{"key":"ref9","author":"fujimoto","year":"2006","journal-title":"CRAWDAD dataset gatech\/vehicular"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/LWC.2018.2795605"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2020.2991401"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/IJCNN.2019.8852464"},{"key":"ref42","article-title":"Performance metrics (error measures) in machine learning regression, forecasting and prognostics: Properties and typology","author":"botchkarev","year":"2018","journal-title":"arXiv 1809 03006"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/YAC.2016.7804912"},{"key":"ref41","first-page":"265","article-title":"On optimization methods for deep learning","author":"le","year":"2011","journal-title":"Proc ICML"},{"key":"ref23","author":"chen","year":"2002","journal-title":"Freeway performance measurement system (pems)"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1016\/j.trc.2015.03.014"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/ICACCI.2017.8126009"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2014.2345663"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6287639\/9668973\/09950054.pdf?arnumber=9950054","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,12,12]],"date-time":"2022-12-12T20:04:24Z","timestamp":1670875464000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9950054\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"references-count":43,"URL":"https:\/\/doi.org\/10.1109\/access.2022.3221970","relation":{},"ISSN":["2169-3536"],"issn-type":[{"value":"2169-3536","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022]]}}}