{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,23]],"date-time":"2026-01-23T18:22:34Z","timestamp":1769192554127,"version":"3.49.0"},"publisher-location":"New York, NY, USA","reference-count":31,"publisher":"ACM","license":[{"start":{"date-parts":[[2019,7,25]],"date-time":"2019-07-25T00:00:00Z","timestamp":1564012800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"National Social Science Foundation of China","award":["18CSH019"],"award-info":[{"award-number":["18CSH019"]}]},{"name":"National Key Research and Development Program of China","award":["2017YFC1501503"],"award-info":[{"award-number":["2017YFC1501503"]}]},{"name":"Beijing Municipal Education Commission Research Program","award":["SM20191001107"],"award-info":[{"award-number":["SM20191001107"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2019,7,25]]},"DOI":"10.1145\/3292500.3330717","type":"proceedings-article","created":{"date-parts":[[2019,7,26]],"date-time":"2019-07-26T13:17:26Z","timestamp":1564147046000},"page":"2439-2447","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":43,"title":["LightNet"],"prefix":"10.1145","author":[{"given":"Yangli-ao","family":"Geng","sequence":"first","affiliation":[{"name":"Beijing Jiaotong University, Beijing, China"}]},{"given":"Qingyong","family":"Li","sequence":"additional","affiliation":[{"name":"Beijing Jiaotong University, Beijing, China"}]},{"given":"Tianyang","family":"Lin","sequence":"additional","affiliation":[{"name":"Beijing Jiaotong University, Beijing, China"}]},{"given":"Lei","family":"Jiang","sequence":"additional","affiliation":[{"name":"Beijing Jiaotong University, Beijing, China"}]},{"given":"Liangtao","family":"Xu","sequence":"additional","affiliation":[{"name":"Chinese Academy of Meteorological Sciences, Beijing, China"}]},{"given":"Dong","family":"Zheng","sequence":"additional","affiliation":[{"name":"Chinese Academy of Meteorological Sciences, Beijing, China"}]},{"given":"Wen","family":"Yao","sequence":"additional","affiliation":[{"name":"Chinese Academy of Meteorological Sciences, Beijing, China"}]},{"given":"Weitao","family":"Lyu","sequence":"additional","affiliation":[{"name":"Chinese Academy of Meteorological Sciences, Beijing, China"}]},{"given":"Yijun","family":"Zhang","sequence":"additional","affiliation":[{"name":"Fudan University, Shanghai, China"}]}],"member":"320","published-online":{"date-parts":[[2019,7,25]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1175\/1520-0450(1964)003<0415:SOOVVA>2.0.CO;2"},{"key":"e_1_3_2_1_2_1","volume-title":"Proc. EMNLP. Association for Computational Linguistics, Doha, Qatar, 1724--1734","author":"Kyunghyun"},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1175\/2010WAF2222404.1"},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1175\/1520-0442(2000)013<3448:LCADIT>2.0.CO;2"},{"key":"e_1_3_2_1_6_1","article-title":"The relationship between lightning activity and ice fluxes in thunderstorms","volume":"113","author":"Wiebke Deierling","year":"2008","journal-title":"Journal of Geophysical Research: Atmospheres"},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.atmosres.2014.12.009"},{"key":"e_1_3_2_1_8_1","volume-title":"Glossary of meteorology","author":"Glickman Todd S"},{"key":"e_1_3_2_1_9_1","volume-title":"Proc. NIPS . 3146--3154","author":"Guolin"},{"key":"e_1_3_2_1_10_1","volume-title":"Kingma and Jimmy Ba","author":"Diederik","year":"2014"},{"key":"e_1_3_2_1_11_1","volume-title":"Proc. IEEE CVPR . 4840--4848","author":"Klein Benjamin","year":"2015"},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1098\/rspa.1961.0052"},{"key":"e_1_3_2_1_13_1","unstructured":"Yunjie Liu et al. 2016. Application of deep convolutional neural networks for detecting extreme weather in climate datasets. arXiv preprint arXiv:1605.01156 (2016).  Yunjie Liu et al. 2016. Application of deep convolutional neural networks for detecting extreme weather in climate datasets. arXiv preprint arXiv:1605.01156 (2016)."},{"key":"e_1_3_2_1_14_1","volume-title":"Michalon","author":"N","year":"1999"},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.178"},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1029\/92JD00719"},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jhazmat.2010.07.118"},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1175\/1520-0469(1957)014<0426:TCS>2.0.CO;2"},{"key":"e_1_3_2_1_19_1","volume-title":"A short course in cloud physics","author":"Rogers R. R.","edition":"3"},{"key":"e_1_3_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1145\/3219819.3219931"},{"key":"e_1_3_2_1_21_1","volume-title":"Proc. NIPS. 802--810","author":"Xingjian"},{"key":"e_1_3_2_1_22_1","volume-title":"Proc. NIPS . 5617--5627","author":"Xingjian"},{"key":"e_1_3_2_1_23_1","unstructured":"W. C. Skamarock etal 2008. A description of the Advanced Research WRF Version 3. Technical Report. National Center for Atmospheric Research. 1--113 pages.  W. C. Skamarock et al. 2008. A description of the Advanced Research WRF Version 3. Technical Report. National Center for Atmospheric Research. 1--113 pages."},{"key":"e_1_3_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.1175\/2008WAF2222152.1"},{"key":"e_1_3_2_1_25_1","unstructured":"Meng Qing et al. 2006. Development of national lightning detection network and its application in China.  Meng Qing et al. 2006. Development of national lightning detection network and its application in China."},{"key":"e_1_3_2_1_26_1","volume-title":"Proc. ICLR .","author":"Yaguang"},{"key":"e_1_3_2_1_27_1","volume-title":"Proc. IJCAI . 2940--2947","author":"Ziru"},{"key":"e_1_3_2_1_28_1","volume-title":"Divide the gradient by a running average of its recent magnitude. COURSERA: Neural networks for machine learning","author":"Tieleman Tijmen","year":"2012"},{"key":"e_1_3_2_1_29_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.510"},{"key":"e_1_3_2_1_30_1","doi-asserted-by":"publisher","DOI":"10.3390\/atmos9030099"},{"key":"e_1_3_2_1_31_1","first-page":"44","article-title":"Progress in lightning forecast by using numerical weather models and model outputs","volume":"32","author":"Haoliang Wang","year":"2017","journal-title":"Advances in Earth Science"},{"key":"e_1_3_2_1_32_1","volume-title":"Proc. NIPS. 879--888","author":"Yunbo"}],"event":{"name":"KDD '19: The 25th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","location":"Anchorage AK USA","acronym":"KDD '19","sponsor":["SIGMOD ACM Special Interest Group on Management of Data","SIGKDD ACM Special Interest Group on Knowledge Discovery in Data"]},"container-title":["Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery &amp; Data Mining"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3292500.3330717","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3292500.3330717","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T00:57:50Z","timestamp":1750208270000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3292500.3330717"}},"subtitle":["A Dual Spatiotemporal Encoder Network Model for Lightning Prediction"],"short-title":[],"issued":{"date-parts":[[2019,7,25]]},"references-count":31,"alternative-id":["10.1145\/3292500.3330717","10.1145\/3292500"],"URL":"https:\/\/doi.org\/10.1145\/3292500.3330717","relation":{},"subject":[],"published":{"date-parts":[[2019,7,25]]},"assertion":[{"value":"2019-07-25","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}