{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,31]],"date-time":"2026-01-31T22:00:59Z","timestamp":1769896859410,"version":"3.49.0"},"reference-count":22,"publisher":"IEEE","license":[{"start":{"date-parts":[[2020,8,1]],"date-time":"2020-08-01T00:00:00Z","timestamp":1596240000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2020,8,1]],"date-time":"2020-08-01T00:00:00Z","timestamp":1596240000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2020,8,1]],"date-time":"2020-08-01T00:00:00Z","timestamp":1596240000000},"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":[[2020,8]]},"DOI":"10.1109\/icaci49185.2020.9177688","type":"proceedings-article","created":{"date-parts":[[2020,8,26]],"date-time":"2020-08-26T20:43:42Z","timestamp":1598474622000},"page":"86-91","source":"Crossref","is-referenced-by-count":9,"title":["Time Series-oriented Load Prediction Using Deep Peephole LSTM"],"prefix":"10.1109","author":[{"given":"Lei","family":"Fu","sequence":"first","affiliation":[]}],"member":"263","reference":[{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1016\/0142-0615(80)90004-6"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijforecast.2006.03.005"},{"key":"ref12","article-title":"Learning Sequence Representations","author":"bayer","year":"2015","journal-title":"Technische Universitt Mnchen"},{"key":"ref13","first-page":"1310","article-title":"On the difficulty of training recurrent neural networks","author":"pascanu","year":"2013","journal-title":"International Conference on Machine Learning"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1997.9.8.1735"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2016.2582924"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1049\/cp:19991218"},{"key":"ref17","first-page":"115","article-title":"Learning precise timing with LSTM recurrent networks","volume":"3","author":"gers","year":"2002","journal-title":"Journal of Machine Learning Research"},{"key":"ref18","doi-asserted-by":"crossref","first-page":"436","DOI":"10.1038\/nature14539","article-title":"Deep learning","volume":"521","author":"lecun","year":"2015","journal-title":"Nature"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1016\/j.petrol.2013.03.004"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.2307\/1912773"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijforecast.2006.01.001"},{"key":"ref6","first-page":"1868","article-title":"Time series prediction using RNN in multidimension embedding phase space","volume":"2","author":"zhang","year":"1998","journal-title":"IEEE International Conference on Systems"},{"key":"ref5","author":"tong","year":"1990","journal-title":"Non-linear Time Series A Dynamical System Approach"},{"key":"ref8","article-title":"How to construct deep recurrent neural networks","author":"pascanu","year":"2014","journal-title":"in Proceedings of the Second International Conference on Learning Representations ICLR"},{"key":"ref7","first-page":"190","article-title":"Training and analyzing deep recurrent neural networks","author":"hermans","year":"2013","journal-title":"in Proceedings of the 26th International Conference on Neural Information Processing Systems NIPS 1"},{"key":"ref2","first-page":"215","article-title":"Time seriesoriented load prediction model and migration policies for distributed simulation systems","volume":"28","author":"alkharboush","year":"2016","journal-title":"IEEE Transactions on Parallel and Distributed Systems"},{"key":"ref1","first-page":"161","article-title":"Load prediction in hla-based distributed simulation using holt’s variants","author":"alkharboush","year":"2013","journal-title":"in Proc of IEEE\/ACM Int Symposium on Distributed Simulation and Real Time Applications"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/TDC.1999.755371"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.2307\/2533213"},{"key":"ref22","first-page":"177","article-title":"Measuring forecast accuracy","author":"hyndman","year":"2014","journal-title":"Business Forecasting Practical Problems and Solutions"},{"key":"ref21","first-page":"1412","article-title":"Empirical evaluation of gated recurrent neural networks on sequence modeling","author":"junyoung","year":"2014","journal-title":"Proceedings of the Deep Learning Workshop at NIPS"}],"event":{"name":"2020 12th International Conference on Advanced Computational Intelligence (ICACI)","location":"Dali, China","start":{"date-parts":[[2020,8,14]]},"end":{"date-parts":[[2020,8,16]]}},"container-title":["2020 12th International Conference on Advanced Computational Intelligence (ICACI)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9171990\/9177495\/09177688.pdf?arnumber=9177688","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,6,28]],"date-time":"2022-06-28T00:22:40Z","timestamp":1656375760000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9177688\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,8]]},"references-count":22,"URL":"https:\/\/doi.org\/10.1109\/icaci49185.2020.9177688","relation":{},"subject":[],"published":{"date-parts":[[2020,8]]}}}