{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,15]],"date-time":"2025-11-15T07:27:47Z","timestamp":1763191667934,"version":"3.45.0"},"reference-count":23,"publisher":"IEEE","license":[{"start":{"date-parts":[[2025,6,30]],"date-time":"2025-06-30T00:00:00Z","timestamp":1751241600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,6,30]],"date-time":"2025-06-30T00:00:00Z","timestamp":1751241600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,6,30]]},"DOI":"10.1109\/ijcnn64981.2025.11227690","type":"proceedings-article","created":{"date-parts":[[2025,11,14]],"date-time":"2025-11-14T18:46:15Z","timestamp":1763145975000},"page":"1-10","source":"Crossref","is-referenced-by-count":0,"title":["The Multi-Period Time Series Forecasting Method Based on Temporal Decoupling: TimeShaper"],"prefix":"10.1109","author":[{"given":"Xinghao","family":"Wang","sequence":"first","affiliation":[{"name":"Zhejiang University,School of Software Technology,Ningbo,China"}]},{"given":"Zhengong","family":"Cai","sequence":"additional","affiliation":[{"name":"Zhejiang University,School of Software Technology,Ningbo,China"}]},{"given":"Bowei","family":"Yang","sequence":"additional","affiliation":[{"name":"Zhejiang University,School of Aeronautics and Astronautics,Hangzhou,China"}]},{"given":"Xinhua","family":"Miao","sequence":"additional","affiliation":[{"name":"Zhejiang University,School of Software Technology,Ningbo,China"}]},{"given":"Aoyu","family":"Wang","sequence":"additional","affiliation":[{"name":"Hangzhou HarmonyCloud Technology Co., Ltd.,Hangzhou,China"}]}],"member":"263","reference":[{"article-title":"Timesnet: Temporal 2d-variation modeling for general time series analysis","year":"2022","author":"Wu","key":"ref1"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52734.2025.01320"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-49409-8_7"},{"article-title":"Timemixer: Decomposable multiscale mixing for time series forecasting","year":"2024","author":"Wang","key":"ref4"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1997.9.8.1735"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/BigData47090.2019.9005997"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1145\/3209978.3210006"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i12.17325"},{"key":"ref9","first-page":"22 419","article-title":"Autoformer: Decomposition transformers with auto-correlation for long-term series forecasting","volume-title":"Advances in neural information processing systems","volume":"34","author":"Wu"},{"article-title":"A time series is worth 64 words: Long-term forecasting with transformers","year":"2022","author":"Nie","key":"ref10"},{"article-title":"itransformer: Inverted transformers are effective for time series forecasting","year":"2023","author":"Liu","key":"ref11"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.52202\/079017-0015"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1145\/3581783.3611910"},{"article-title":"Less is more: Fast multivariate time series forecasting with light sampling-oriented mlp structures","year":"2022","author":"Zhang","key":"ref14"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v37i9.26317"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2024.3430860"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.4324\/9781410605337-29"},{"article-title":"Wavenet: A generative model for raw audio","year":"2016","author":"Oord","key":"ref19"},{"article-title":"Multi-scale context aggregation by dilated convolutions","year":"2015","author":"Yu","key":"ref20"},{"key":"ref21","article-title":"Weight normalization: A simple reparameterization to accelerate training of deep neural networks","volume-title":"Advances in neural information processing systems","volume":"29","author":"Salimans"},{"key":"ref22","first-page":"807","article-title":"Rectified linear units improve restricted boltzmann machines","volume-title":"Proceedings of the 27th international conference on machine learning (ICML-10)","author":"Nair"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1080\/00031305.2017.1380080"}],"event":{"name":"2025 International Joint Conference on Neural Networks (IJCNN)","start":{"date-parts":[[2025,6,30]]},"location":"Rome, Italy","end":{"date-parts":[[2025,7,5]]}},"container-title":["2025 International Joint Conference on Neural Networks (IJCNN)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/11227166\/11227148\/11227690.pdf?arnumber=11227690","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,11,15]],"date-time":"2025-11-15T07:23:15Z","timestamp":1763191395000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11227690\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,6,30]]},"references-count":23,"URL":"https:\/\/doi.org\/10.1109\/ijcnn64981.2025.11227690","relation":{},"subject":[],"published":{"date-parts":[[2025,6,30]]}}}