{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,24]],"date-time":"2026-06-24T14:03:47Z","timestamp":1782309827591,"version":"3.54.5"},"publisher-location":"New York, NY, USA","reference-count":13,"publisher":"ACM","license":[{"start":{"date-parts":[[2019,4,12]],"date-time":"2019-04-12T00:00:00Z","timestamp":1555027200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2019,4,12]]},"DOI":"10.1145\/3325730.3325735","type":"proceedings-article","created":{"date-parts":[[2019,6,21]],"date-time":"2019-06-21T12:45:07Z","timestamp":1561121107000},"page":"85-89","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":25,"title":["Wind Power Generation Prediction Based on LSTM"],"prefix":"10.1145","author":[{"given":"Jinxia","family":"Zhang","sequence":"first","affiliation":[{"name":"Beijing Advanced Innovation Center for Future Network Technology, Beijing University of Technology, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xuru","family":"Jiang","sequence":"additional","affiliation":[{"name":"State Power Investment China Electric Power Complete Equipment Co., Ltd. Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xin","family":"Chen","sequence":"additional","affiliation":[{"name":"State Grid Gansu Electric Power Company, Gansu, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaojing","family":"Li","sequence":"additional","affiliation":[{"name":"State Grid Gansu Electric Power Company, Gansu, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dong","family":"Guo","sequence":"additional","affiliation":[{"name":"Beijing Guotong Network Technology Co., Ltd., Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lixin","family":"Cui","sequence":"additional","affiliation":[{"name":"State Grid Gansu Electric Power CompanyGansu, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2019,4,12]]},"reference":[{"key":"e_1_3_2_1_1_1","first-page":"012","article-title":"Research on Short-term Wind Power Prediction","volume":"1","year":"2013","unstructured":"FAN, H., CHEN, C., & JIN, Y. ( 2013 ). Research on Short-term Wind Power Prediction . Journal of Shanghai University of Electric Power , 1 , 012 . FAN, H., CHEN, C., & JIN, Y. (2013). Research on Short-term Wind Power Prediction. Journal of Shanghai University of Electric Power, 1, 012.","journal-title":"Journal of Shanghai University of Electric Power"},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1109\/60.556371"},{"key":"e_1_3_2_1_3_1","volume-title":"Short Term Prodiction of Wind Power Based on Time Series Modeling","year":"2016","unstructured":"TIAN, B., PIAO, Z., & WANG, H. ( 2016 ). Short Term Prodiction of Wind Power Based on Time Series Modeling . TIAN, B., PIAO, Z., & WANG, H. (2016). Short Term Prodiction of Wind Power Based on Time Series Modeling."},{"issue":"6","key":"e_1_3_2_1_4_1","first-page":"75","article-title":"Analysis and forecast of wind power fluctuation based on symbolized time series theory","volume":"46","year":"2013","unstructured":"NAN, X., LI, Q., & QIU, D. ( 2013 ). Analysis and forecast of wind power fluctuation based on symbolized time series theory . Electric Power , 46 ( 6 ), 75 -- 79 . NAN, X., LI, Q., & QIU, D. (2013). Analysis and forecast of wind power fluctuation based on symbolized time series theory. Electric Power, 46(6), 75--79.","journal-title":"Electric Power"},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1016\/0026-2714(95)00154-9"},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.epsr.2005.01.006"},{"key":"e_1_3_2_1_7_1","volume-title":"Deep learning. nature, 521(7553), 436","author":"LeCun Y.","year":"2015","unstructured":"LeCun , Y. , Bengio , Y. , & Hinton , G. ( 2015 ). Deep learning. nature, 521(7553), 436 . LeCun, Y., Bengio, Y., & Hinton, G. (2015). Deep learning. nature, 521(7553), 436."},{"key":"e_1_3_2_1_8_1","first-page":"2","article-title":"Study on the time-series wind speed forecasting of the wind farm based on neural networks","volume":"2","author":"Xiao Y. S.","year":"2007","unstructured":"Xiao , Y. S. , Wang , W. Q. , & Huo , X. P. ( 2007 ). Study on the time-series wind speed forecasting of the wind farm based on neural networks . Energy Conservation Technology , 2 , 2 . Xiao, Y. S., Wang, W. Q., & Huo, X. P. (2007). Study on the time-series wind speed forecasting of the wind farm based on neural networks. Energy Conservation Technology, 2, 2.","journal-title":"Energy Conservation Technology"},{"issue":"10","key":"e_1_3_2_1_9_1","first-page":"1445","article-title":"A survey on deep learning for natural language processing","volume":"42","author":"XueFeng X.","year":"2016","unstructured":"XueFeng , X. , & Guo-Dong , Z. ( 2016 ). A survey on deep learning for natural language processing . Acta Automatica Sinica , 42 ( 10 ), 1445 -- 1465 . XueFeng, X., & Guo-Dong, Z. (2016). A survey on deep learning for natural language processing. Acta Automatica Sinica, 42(10), 1445--1465.","journal-title":"Acta Automatica Sinica"},{"key":"e_1_3_2_1_10_1","volume-title":"Speech and Signal Processing (ICASSP), 2013 IEEE International Conference on (pp. 8599--8603)","author":"Deng L.","year":"2013","unstructured":"Deng , L. , Hinton , G. , & Kingsbury , B. ( 2013 , May). New types of deep neural network learning for speech recognition and related applications: An overview. In Acoustics , Speech and Signal Processing (ICASSP), 2013 IEEE International Conference on (pp. 8599--8603) . IEEE. Deng, L., Hinton, G., & Kingsbury, B. (2013, May). New types of deep neural network learning for speech recognition and related applications: An overview. In Acoustics, Speech and Signal Processing (ICASSP), 2013 IEEE International Conference on (pp. 8599--8603). IEEE."},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1997.9.8.1735"},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"crossref","unstructured":"Andr\u00e9 Gensler Janosch Henze Bernhard Sick and Nils Raabe \"Deep learning for solar power forecasting - an approach using AutoEncoder and LSTM neural networks \" 2016 IEEE International Conference on Systems Man and Cybernetics pp. 2858--2865 2016.  Andr\u00e9 Gensler Janosch Henze Bernhard Sick and Nils Raabe \"Deep learning for solar power forecasting - an approach using AutoEncoder and LSTM neural networks \" 2016 IEEE International Conference on Systems Man and Cybernetics pp. 2858--2865 2016.","DOI":"10.1109\/SMC.2016.7844673"},{"key":"e_1_3_2_1_13_1","volume-title":"GermanWindFarmData Set","author":"Gensler J.","year":"2016","unstructured":"A. Gensler , J. Henze , N. Raabe , and V. Pankraz , \" GermanWindFarmData Set , 2016 . {Online}. Available: http:\/\/ies-research.de\/Software. A. Gensler, J. Henze, N. Raabe, and V. Pankraz, \"GermanWindFarmData Set, 2016. {Online}. Available: http:\/\/ies-research.de\/Software."}],"event":{"name":"ICMAI 2019: 2019 4th International Conference on Mathematics and Artificial Intelligence","location":"Chegndu China","acronym":"ICMAI 2019","sponsor":["Southwest Jiaotong University","Xihua University Xihua University"]},"container-title":["Proceedings of the 2019 4th International Conference on Mathematics and Artificial Intelligence"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3325730.3325735","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3325730.3325735","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T23:54:22Z","timestamp":1750204462000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3325730.3325735"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,4,12]]},"references-count":13,"alternative-id":["10.1145\/3325730.3325735","10.1145\/3325730"],"URL":"https:\/\/doi.org\/10.1145\/3325730.3325735","relation":{},"subject":[],"published":{"date-parts":[[2019,4,12]]},"assertion":[{"value":"2019-04-12","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}