{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,10,30]],"date-time":"2024-10-30T09:11:30Z","timestamp":1730279490790,"version":"3.28.0"},"reference-count":10,"publisher":"IEEE","license":[{"start":{"date-parts":[[2021,6,28]],"date-time":"2021-06-28T00:00:00Z","timestamp":1624838400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2021,6,28]],"date-time":"2021-06-28T00:00:00Z","timestamp":1624838400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2021,6,28]],"date-time":"2021-06-28T00:00:00Z","timestamp":1624838400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021,6,28]]},"DOI":"10.1109\/iwcmc51323.2021.9498910","type":"proceedings-article","created":{"date-parts":[[2021,8,9]],"date-time":"2021-08-09T22:27:05Z","timestamp":1628548025000},"page":"1683-1688","source":"Crossref","is-referenced-by-count":8,"title":["Accurate Load Prediction Algorithms Assisted with Machine Learning for Network Traffic"],"prefix":"10.1109","author":[{"given":"Yin","family":"Gao","sequence":"first","affiliation":[]},{"given":"Man","family":"Zhang","sequence":"additional","affiliation":[]},{"given":"Jiajun","family":"Chen","sequence":"additional","affiliation":[]},{"given":"Jiren","family":"Han","sequence":"additional","affiliation":[]},{"given":"Dapeng","family":"Li","sequence":"additional","affiliation":[]},{"given":"Ruitao","family":"Qiu","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"journal-title":"XGBoost A Scalable Tree Boosting System","year":"2016","author":"chen","key":"ref4"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/EITCE47263.2019.9094776"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.243"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1002\/ett.2583"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2017.11.053"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1016\/j.enpol.2012.05.026"},{"key":"ref7","article-title":"Traffic prediction based power saving in cellular networks: A machine learning method","author":"zhao","year":"0","journal-title":"the 25th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems"},{"key":"ref2","doi-asserted-by":"crossref","first-page":"1656","DOI":"10.1109\/LCOMM.2018.2841832","article-title":"Citywide cellular traffic prediction based on densely connected convolutional neural networks","volume":"22","author":"chuanting","year":"2018","journal-title":"IEEE Communications Letters"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1198\/jasa.2002.s477"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.12720\/jcm.13.11.627-634"}],"event":{"name":"2021 International Wireless Communications and Mobile Computing (IWCMC)","start":{"date-parts":[[2021,6,28]]},"location":"Harbin City, China","end":{"date-parts":[[2021,7,2]]}},"container-title":["2021 International Wireless Communications and Mobile Computing (IWCMC)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9497780\/9498576\/09498910.pdf?arnumber=9498910","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,5,10]],"date-time":"2022-05-10T15:48:22Z","timestamp":1652197702000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9498910\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,6,28]]},"references-count":10,"URL":"https:\/\/doi.org\/10.1109\/iwcmc51323.2021.9498910","relation":{},"subject":[],"published":{"date-parts":[[2021,6,28]]}}}