{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,14]],"date-time":"2026-03-14T05:45:26Z","timestamp":1773467126094,"version":"3.50.1"},"publisher-location":"New York, NY, USA","reference-count":49,"publisher":"ACM","license":[{"start":{"date-parts":[[2022,6,28]],"date-time":"2022-06-28T00:00:00Z","timestamp":1656374400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100009318","name":"Helmholtz Association","doi-asserted-by":"publisher","award":["Program ?Energy System Design?"],"award-info":[{"award-number":["Program ?Energy System Design?"]}],"id":[{"id":"10.13039\/501100009318","id-type":"DOI","asserted-by":"publisher"}]},{"name":"German Research Foundation (DFG)","award":["Research Training Group 2153 ?Energy Status Data: Informatics Methods for its Collection, Analysis and Exploitation?"],"award-info":[{"award-number":["Research Training Group 2153 ?Energy Status Data: Informatics Methods for its Collection, Analysis and Exploitation?"]}]},{"name":"Helmholtz Association?s Initiative and Networking Fund","award":["Helmholtz AI"],"award-info":[{"award-number":["Helmholtz AI"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2022,6,28]]},"DOI":"10.1145\/3538637.3539760","type":"proceedings-article","created":{"date-parts":[[2022,6,22]],"date-time":"2022-06-22T16:33:05Z","timestamp":1655915585000},"page":"471-484","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":13,"title":["Modeling and generating synthetic anomalies for energy and power time series"],"prefix":"10.1145","author":[{"given":"Marian","family":"Turowski","sequence":"first","affiliation":[{"name":"Karlsruhe Institute of Technology, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Moritz","family":"Weber","sequence":"additional","affiliation":[{"name":"Karlsruhe Institute of Technology, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Oliver","family":"Neumann","sequence":"additional","affiliation":[{"name":"Karlsruhe Institute of Technology, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Benedikt","family":"Heidrich","sequence":"additional","affiliation":[{"name":"Karlsruhe Institute of Technology, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kaleb","family":"Phipps","sequence":"additional","affiliation":[{"name":"Karlsruhe Institute of Technology, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"H\u00fcseyin K.","family":"\u00c7akmak","sequence":"additional","affiliation":[{"name":"Karlsruhe Institute of Technology, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ralf","family":"Mikut","sequence":"additional","affiliation":[{"name":"Karlsruhe Institute of Technology, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Veit","family":"Hagenmeyer","sequence":"additional","affiliation":[{"name":"Karlsruhe Institute of Technology, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2022,6,28]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2015.2414355"},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1201\/9781315139470"},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1145\/1541880.1541882"},{"key":"e_1_3_2_1_4_1","unstructured":"Fran\u00e7ois Chollet et al. 2015. Keras. https:\/\/keras.io.  Fran\u00e7ois Chollet et al. 2015. Keras. https:\/\/keras.io."},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIT.1967.1053964"},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1109\/EESMS.2015.7175886"},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.5555\/3001460.3001507"},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2020.02.069"},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.apenergy.2017.12.005"},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10115-003-0132-7"},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1007\/s41060-021-00265-1"},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2019.2915641"},{"key":"e_1_3_2_1_13_1","volume-title":"pyWATTS: Python Workflow Automation Tool for Time Series. arXiv:2106.10157","author":"Heidrich Benedikt","year":"2021","unstructured":"Benedikt Heidrich , Andreas Bartschat , Marian Turowski , Oliver Neumann , Kaleb Phipps , Stefan Meisenbacher , Kai Schmieder , Nicole Ludwig , Ralf Mikut , and Veit Hagenmeyer . 2021. pyWATTS: Python Workflow Automation Tool for Time Series. arXiv:2106.10157 ( 2021 ). Benedikt Heidrich, Andreas Bartschat, Marian Turowski, Oliver Neumann, Kaleb Phipps, Stefan Meisenbacher, Kai Schmieder, Nicole Ludwig, Ralf Mikut, and Veit Hagenmeyer. 2021. pyWATTS: Python Workflow Automation Tool for Time Series. arXiv:2106.10157 (2021)."},{"key":"e_1_3_2_1_14_1","unstructured":"Benedikt Heidrich Marian Turowski Kaleb Phipps Kai Schmieder Wolfgang S\u00fc\u00df Ralf Mikut and Veit Hagenmeyer. under Review. Controlling Non-Stationarity and Periodicities in Time Series Generation. Applied Intelligence (under Review).  Benedikt Heidrich Marian Turowski Kaleb Phipps Kai Schmieder Wolfgang S\u00fc\u00df Ralf Mikut and Veit Hagenmeyer. under Review. Controlling Non-Stationarity and Periodicities in Time Series Generation. Applied Intelligence (under Review)."},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1007\/s12559-020-09764-y"},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.enbuild.2020.110404"},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.apenergy.2021.116601"},{"key":"e_1_3_2_1_18_1","unstructured":"Geoffrey Hinton Nitish Srivastava and Kevin Swersky. 2012. Neural Networks for Machine Learning Lecture: Lecture 6a Overview of mini-batch gradient descent. http:\/\/www.cs.toronto.edu\/{~}tijmen\/csc321\/slides\/lecture{_}slides{_}lec6.pdf  Geoffrey Hinton Nitish Srivastava and Kevin Swersky. 2012. Neural Networks for Machine Learning Lecture: Lecture 6a Overview of mini-batch gradient descent. http:\/\/www.cs.toronto.edu\/{~}tijmen\/csc321\/slides\/lecture{_}slides{_}lec6.pdf"},{"key":"e_1_3_2_1_19_1","volume-title":"Hyndman and George Athanasopoulos","author":"Rob","year":"2021","unstructured":"Rob J. Hyndman and George Athanasopoulos . 2021 . Forecasting : Principles and Practice (third ed.). OTexts Melbourne, Australia . https:\/\/otexts.com\/fpp3\/ Rob J. Hyndman and George Athanasopoulos. 2021. Forecasting: Principles and Practice (third ed.). OTexts Melbourne, Australia. https:\/\/otexts.com\/fpp3\/"},{"key":"e_1_3_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1109\/IE.2010.13"},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1109\/TSG.2015.2425222"},{"key":"e_1_3_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1007\/s13748-016-0094-0"},{"key":"e_1_3_2_1_23_1","volume-title":"AnoGen: Deep Anomaly Generator. In Outlier Detection De-constructed (ODD) Workshop (ODD v5.0). https:\/\/doi.org\/10","author":"Laptev Nikolay","year":"2018","unstructured":"Nikolay Laptev . 2018 . AnoGen: Deep Anomaly Generator. In Outlier Detection De-constructed (ODD) Workshop (ODD v5.0). https:\/\/doi.org\/10 .475\/123 10.475\/123 Nikolay Laptev. 2018. AnoGen: Deep Anomaly Generator. In Outlier Detection De-constructed (ODD) Workshop (ODD v5.0). https:\/\/doi.org\/10.475\/123"},{"key":"e_1_3_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.1109\/TSG.2010.2053726"},{"key":"e_1_3_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIE.2009.2027926"},{"key":"e_1_3_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1109\/JSEN.2021.3069452"},{"key":"e_1_3_2_1_27_1","doi-asserted-by":"publisher","DOI":"10.1007\/s40565-017-0351-7"},{"key":"e_1_3_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.1109\/TSG.2017.2697440"},{"key":"e_1_3_2_1_29_1","doi-asserted-by":"publisher","DOI":"10.1145\/1525856.1525863"},{"key":"e_1_3_2_1_30_1","doi-asserted-by":"publisher","DOI":"10.1145\/3439950"},{"key":"e_1_3_2_1_31_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-24177-7_20"},{"key":"e_1_3_2_1_32_1","doi-asserted-by":"publisher","DOI":"10.5555\/1953048.2078195"},{"key":"e_1_3_2_1_33_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICMLA.2018.00207"},{"key":"e_1_3_2_1_34_1","doi-asserted-by":"publisher","DOI":"10.1145\/2676585.2676618"},{"key":"e_1_3_2_1_35_1","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2019.2954098"},{"key":"e_1_3_2_1_36_1","doi-asserted-by":"publisher","DOI":"10.1109\/JPROC.2021.3052449"},{"key":"e_1_3_2_1_37_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.enbuild.2006.03.033"},{"key":"e_1_3_2_1_38_1","doi-asserted-by":"publisher","DOI":"10.1145\/1754414.1754419"},{"key":"e_1_3_2_1_39_1","doi-asserted-by":"publisher","DOI":"10.1145\/3447822"},{"key":"e_1_3_2_1_40_1","first-page":"2579","article-title":"Visualizing Data using t-SNE","volume":"9","author":"van der Maaten Laurens","year":"2008","unstructured":"Laurens van der Maaten and Geoffrey Hinton . 2008 . Visualizing Data using t-SNE . Journal of Machine Learning Research 9 , 86 (2008), 2579 -- 2605 . http:\/\/jmlr.org\/papers\/v9\/vandermaaten08a.html Laurens van der Maaten and Geoffrey Hinton. 2008. Visualizing Data using t-SNE. Journal of Machine Learning Research 9, 86 (2008), 2579--2605. http:\/\/jmlr.org\/papers\/v9\/vandermaaten08a.html","journal-title":"Journal of Machine Learning Research"},{"key":"e_1_3_2_1_41_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.energy.2017.07.008"},{"key":"e_1_3_2_1_42_1","doi-asserted-by":"publisher","DOI":"10.1109\/TNSM.2021.3098784"},{"key":"e_1_3_2_1_43_1","doi-asserted-by":"publisher","DOI":"10.1109\/ISC2.2017.8090823"},{"key":"e_1_3_2_1_44_1","doi-asserted-by":"publisher","DOI":"10.1109\/TSG.2018.2818167"},{"key":"e_1_3_2_1_45_1","doi-asserted-by":"publisher","DOI":"10.1109\/TSG.2021.3101831"},{"key":"e_1_3_2_1_46_1","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2021\/631"},{"key":"e_1_3_2_1_47_1","doi-asserted-by":"publisher","DOI":"10.1109\/epec52095.2021.9621752"},{"key":"e_1_3_2_1_48_1","doi-asserted-by":"publisher","DOI":"10.1109\/19.963215"},{"key":"e_1_3_2_1_49_1","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2019\/616"}],"event":{"name":"e-Energy '22: The Thirteenth ACM International Conference on Future Energy Systems","location":"Virtual Event","acronym":"e-Energy '22","sponsor":["SIGEnergy ACM Special Interest Group on Energy Systems and Informatics"]},"container-title":["Proceedings of the Thirteenth ACM International Conference on Future Energy Systems"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3538637.3539760","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3538637.3539760","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T19:03:02Z","timestamp":1750186982000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3538637.3539760"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,6,28]]},"references-count":49,"alternative-id":["10.1145\/3538637.3539760","10.1145\/3538637"],"URL":"https:\/\/doi.org\/10.1145\/3538637.3539760","relation":{},"subject":[],"published":{"date-parts":[[2022,6,28]]},"assertion":[{"value":"2022-06-28","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}