{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,14]],"date-time":"2026-01-14T17:32:59Z","timestamp":1768411979376,"version":"3.49.0"},"reference-count":17,"publisher":"Springer Science and Business Media LLC","issue":"4","license":[{"start":{"date-parts":[[2020,3,9]],"date-time":"2020-03-09T00:00:00Z","timestamp":1583712000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2020,3,9]],"date-time":"2020-03-09T00:00:00Z","timestamp":1583712000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Sci. China Inf. Sci."],"published-print":{"date-parts":[[2020,4]]},"DOI":"10.1007\/s11432-019-2695-6","type":"journal-article","created":{"date-parts":[[2020,3,16]],"date-time":"2020-03-16T05:09:43Z","timestamp":1584335383000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":27,"title":["Prophet model and Gaussian process regression based user traffic prediction in wireless networks"],"prefix":"10.1007","volume":"63","author":[{"given":"Yu","family":"Li","sequence":"first","affiliation":[]},{"given":"Ziang","family":"Ma","sequence":"additional","affiliation":[]},{"given":"Zhiwen","family":"Pan","sequence":"additional","affiliation":[]},{"given":"Nan","family":"Liu","sequence":"additional","affiliation":[]},{"given":"Xiaohu","family":"You","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2020,3,9]]},"reference":[{"key":"2695_CR1","doi-asserted-by":"publisher","first-page":"124","DOI":"10.1109\/COMST.2015.2491361","volume":"18","author":"D Naboulsi","year":"2016","unstructured":"Naboulsi D, Fiore M, Ribot S, et al. Large-scale mobile traffic analysis: a survey. IEEE Commun Surv Tut, 2016, 18: 124\u2013161","journal-title":"IEEE Commun Surv Tut"},{"key":"2695_CR2","doi-asserted-by":"publisher","first-page":"796","DOI":"10.1109\/TSC.2016.2599878","volume":"9","author":"F L Xu","year":"2016","unstructured":"Xu F L, Lin Y Y, Huang J X, et al. Big data driven mobile traffic understanding and forecasting: a time series approach. IEEE Trans Serv Comput, 2016, 9: 796\u2013805","journal-title":"IEEE Trans Serv Comput"},{"key":"2695_CR3","doi-asserted-by":"crossref","unstructured":"Le L, Sinh D, Tung L, et al. A practical model for traffic forecasting based on big data, machine-learning, and network KPIs. In: Proceedings of IEEE Annual Consumer Communications and Networking Conference (CCNC), Las Vegas, 2018. 1\u20134","DOI":"10.1109\/CCNC.2018.8319255"},{"key":"2695_CR4","doi-asserted-by":"crossref","unstructured":"Le L, Sinh D, Lin B P, et al. Applying big data, machine learning, and SDN\/NFV to 5G traffic clustering, forecasting, and management. In: Proceedings of IEEE Conference on Network Softwarization and Workshops (NetSoft), Montreal, 2018. 168\u2013176","DOI":"10.1109\/NETSOFT.2018.8460129"},{"key":"2695_CR5","doi-asserted-by":"publisher","first-page":"3091","DOI":"10.1109\/JIOT.2018.2832071","volume":"5","author":"L Y Fang","year":"2018","unstructured":"Fang L Y, Cheng X, Wang H N, et al. Mobile demand forecasting via deep graph-sequence spatiotemporal modeling in cellular networks. IEEE Internet Things J, 2018, 5: 3091\u20133101","journal-title":"IEEE Internet Things J"},{"key":"2695_CR6","doi-asserted-by":"crossref","unstructured":"Dawoud S, Uzun A, G\u00f6nd\u00f6r S, et al. Optimizing the power consumption of mobile networks based on traffic prediction. In: Proceedings of IEEE 38th Annual Computer Software and Applications Conference, Vasteras, 2014. 279\u2013288","DOI":"10.1109\/COMPSAC.2014.38"},{"key":"2695_CR7","doi-asserted-by":"crossref","unstructured":"Hu J M, Heng W, Zhang G D, et al. Base station sleeping mechanism based on traffic prediction in heterogeneous networks. In: Proceedings of International Telecommunication Networks and Applications Conference (ITNAC), Sydney, 2015. 83\u201387","DOI":"10.1109\/ATNAC.2015.7366793"},{"key":"2695_CR8","doi-asserted-by":"publisher","first-page":"95","DOI":"10.1109\/TETC.2014.2381512","volume":"3","author":"J Yang","year":"2015","unstructured":"Yang J, Qiao Y Y, Zhang X Y, et al. Characterizing user behavior in mobile Internet. IEEE Trans Emerg Top Comput, 2015, 3: 95\u2013106","journal-title":"IEEE Trans Emerg Top Comput"},{"key":"2695_CR9","doi-asserted-by":"crossref","unstructured":"He G H, Hou J C, Chen W-P, et al. Characterizing individual user behaviors in wlans. In: Proceedings of 10th ACM Symposium on Modeling, Analysis, and Simulation of Wireless and Mobile Systems (MSWiM), Chania, 2007. 132\u2013137","DOI":"10.1145\/1298126.1298150"},{"key":"2695_CR10","doi-asserted-by":"crossref","unstructured":"Nie L, Jiang D D, Yu S, et al. Network traffic prediction based on deep belief network in wireless mesh backbone networks. In: Proceedings of IEEE Wireless Communications and Networking Conference (WCNC), San Francisco, 2017. 1\u20135","DOI":"10.1109\/WCNC.2017.7925498"},{"key":"2695_CR11","doi-asserted-by":"publisher","first-page":"507","DOI":"10.1109\/TNSE.2018.2877597","volume":"7","author":"D D Jiang","year":"2020","unstructured":"Jiang D D, Wang W J, Shi L, et al. A compressive sensing-based approach to end-to-end network traffic reconstruction. IEEE Trans Netw Sci Eng, 2020, 7: 507\u2013519","journal-title":"IEEE Trans Netw Sci Eng"},{"key":"2695_CR12","first-page":"e4092","volume":"56","author":"L W Huo","year":"2019","unstructured":"Huo L W, Jiang D D, Zhu X N, et al. A SDN-based fine-grained measurement and modeling approach to vehicular communication network traffic. Int J Commun Syst, 2019, 56: e4092","journal-title":"Int J Commun Syst"},{"key":"2695_CR13","doi-asserted-by":"crossref","unstructured":"Wu J, Zeng M, Chen X L. Characterizing and predicting individual traffic usage of mobile application in cellular network. In: Proceedings of ACM International Joint Conference and International Symposium on Pervasive and Ubiquitous Computing and Wearable Computers (UbiComp18), New York, 2018. 852\u2013861","DOI":"10.1145\/3267305.3274173"},{"key":"2695_CR14","doi-asserted-by":"crossref","unstructured":"Lai Y-T, Wu Y-P, Yu C-H, et al. Mobile data usage prediction system and method. In: Proceedings of 31st International Conference on Advanced Information Networking and Applications Workshops (WAINA), Taipei, 2017. 484\u2013486","DOI":"10.1109\/WAINA.2017.50"},{"key":"2695_CR15","doi-asserted-by":"publisher","first-page":"37","DOI":"10.1080\/00031305.2017.1380080","volume":"72","author":"S J Taylor","year":"2018","unstructured":"Taylor S J, Letham B. Forecasting at scale. Am Stat, 2018, 72: 37\u201345","journal-title":"Am Stat"},{"key":"2695_CR16","doi-asserted-by":"crossref","unstructured":"Xu M, Wang Q L, Lin Q L. Hybrid holiday traffic predictions in cellular networks. In: Proceedings of IEEE\/IFIP Network Operations and Management Symposium, Taipei, 2018. 1\u20136","DOI":"10.1109\/NOMS.2018.8406291"},{"key":"2695_CR17","doi-asserted-by":"publisher","first-page":"51","DOI":"10.1109\/MCI.2017.2773824","volume":"13","author":"J Riihijarvi","year":"2018","unstructured":"Riihijarvi J, Mahonen P. Machine learning for performance prediction in mobile cellular networks. IEEE Comput Intell Mag, 2018, 13: 51\u201360","journal-title":"IEEE Comput Intell Mag"}],"container-title":["Science China Information Sciences"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11432-019-2695-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11432-019-2695-6\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11432-019-2695-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,4,11]],"date-time":"2023-04-11T14:46:06Z","timestamp":1681224366000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11432-019-2695-6"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,3,9]]},"references-count":17,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2020,4]]}},"alternative-id":["2695"],"URL":"https:\/\/doi.org\/10.1007\/s11432-019-2695-6","relation":{},"ISSN":["1674-733X","1869-1919"],"issn-type":[{"value":"1674-733X","type":"print"},{"value":"1869-1919","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,3,9]]},"assertion":[{"value":"16 June 2019","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"6 August 2019","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"25 October 2019","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"9 March 2020","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}],"article-number":"142301"}}