{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,11]],"date-time":"2026-04-11T03:52:38Z","timestamp":1775879558079,"version":"3.50.1"},"reference-count":35,"publisher":"Wiley","issue":"7","license":[{"start":{"date-parts":[[2026,3,19]],"date-time":"2026-03-19T00:00:00Z","timestamp":1773878400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"},{"start":{"date-parts":[[2026,3,19]],"date-time":"2026-03-19T00:00:00Z","timestamp":1773878400000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Concurrency and Computation"],"published-print":{"date-parts":[[2026,4]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:p>Olympic Games are world's mainly important sporting event, in which athletes from every country have an opportunity to compete across a wide range of disciplines for prize money and recognition. The objective of the game is to examine how a nation's socioeconomic characteristics affect its overall performance at the Olympics, as indicated by count of medals achieved. In order to identify key socioeconomic success factors, the analysis includes modeling to forecast a nation's success. This work can help explain why certain nations win a disproportionate number of medals in certain events while others do not participate at all. Principal goal of this work is to create a deep learning (DL) technique for predicting distribution of Olympic medals. In the beginning, the input data is cleaned and then normalized. The suggested double exponential smoothing osprey optimization algorithm (DESOOA), which was proposed by incorporating the double exponential smoothing idea into the osprey optimization algorithm, is employed to choose features. Olympic medal distribution forecasting is executed using the combined form of variational autoencoder (VAE) and deep residual networks (DRN). Using the proposed VAE\u2010DRN, the Olympic medal distribution forecasting is completed following the selection of significant features. The experimental findings state that the presented mechanism outperformed other traditional strategies in case of accuracy (95.6%), sensitivity (97.3%), specificity (93.8%), and F\u2010measure (95.5%).<\/jats:p>","DOI":"10.1002\/cpe.70653","type":"journal-article","created":{"date-parts":[[2026,3,20]],"date-time":"2026-03-20T03:34:16Z","timestamp":1773977656000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Variable Autoencoder\u2010Deep Residual Network With Optimized Feature Selection Approach for Olympic Medal Distribution Forecast"],"prefix":"10.1002","volume":"38","author":[{"ORCID":"https:\/\/orcid.org\/0009-0006-7868-8564","authenticated-orcid":false,"given":"Qian","family":"Wang","sequence":"first","affiliation":[{"name":"School of Physical Education Hunan University of Science and Technology  Xiangtan People's Republic of China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xuefeng","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Physical Education Hunan University of Science and Technology  Xiangtan People's Republic of China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wenbo","family":"Shi","sequence":"additional","affiliation":[{"name":"School of Physical Education Hunan University of Science and Technology  Xiangtan People's Republic of China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Huaifei","family":"Cai","sequence":"additional","affiliation":[{"name":"School of Physical Education Hunan University of Science and Technology  Xiangtan People's Republic of China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2026,3,19]]},"reference":[{"key":"e_1_2_9_2_1","doi-asserted-by":"publisher","DOI":"10.3390\/technologies13060250"},{"key":"e_1_2_9_3_1","doi-asserted-by":"publisher","DOI":"10.3389\/fmech.2022.1126450"},{"key":"e_1_2_9_4_1","doi-asserted-by":"publisher","DOI":"10.1515\/jaiscr-2018-0011"},{"key":"e_1_2_9_5_1","doi-asserted-by":"publisher","DOI":"10.1123\/ijspp.8.2.203"},{"key":"e_1_2_9_6_1","doi-asserted-by":"publisher","DOI":"10.1111\/ssqu.12782"},{"key":"e_1_2_9_7_1","doi-asserted-by":"crossref","unstructured":"C.Schlembach S. L.Schmidt D.Schreyer andL.Wunderlich \u201cForecasting the Olympic Medal Distribution During a Pandemic: A Socio\u2010Economic Machine Learning Model \u201d(2020) 2012.04378.","DOI":"10.2139\/ssrn.3745595"},{"key":"e_1_2_9_8_1","first-page":"55","volume-title":"International Conference on ICT Innovations","author":"Zdravevski E.","year":"2009"},{"issue":"3","key":"e_1_2_9_9_1","first-page":"195","article-title":"Olympic Medals: Success Predictions for R\u00edo\u20102016","volume":"38","author":"Sanchez\u2010Fernandez P.","year":"2016","journal-title":"South African Journal for Research in Sport Physical Education and Recreation"},{"key":"e_1_2_9_10_1","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0101796"},{"key":"e_1_2_9_11_1","unstructured":"C. P.Igiri \u201cSupport Vector Machine\u2013Based Prediction System for a Football Match Result \u201d(2015)."},{"key":"e_1_2_9_12_1","doi-asserted-by":"publisher","DOI":"10.1504\/IJEPEE.2013.057908"},{"key":"e_1_2_9_13_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.techfore.2021.121314"},{"key":"e_1_2_9_14_1","doi-asserted-by":"publisher","DOI":"10.1007\/s40745-018-00189-x"},{"key":"e_1_2_9_15_1","first-page":"2024","article-title":"Possible Impact of National Responses to the COVID Pandemic on Medal Tallies at the Paris 2024 Olympics","volume":"8","author":"Orchard J. W.","year":"2024","journal-title":"medRxiv"},{"key":"e_1_2_9_16_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijforecast.2018.01.003"},{"key":"e_1_2_9_17_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10559-005-0098-4"},{"key":"e_1_2_9_18_1","unstructured":"Y.Wang J.Wang T.\u2010Y.Huang J.Yang andZ.Xu \u201cSTGCN\u2010LSTM for Olympic Medal Prediction \u201d(2025) arXiv preprint arXiv:2501.17711."},{"key":"e_1_2_9_19_1","doi-asserted-by":"publisher","DOI":"10.3390\/ijerph19042110"},{"key":"e_1_2_9_20_1","doi-asserted-by":"publisher","DOI":"10.4337\/9780857930279.00020"},{"key":"e_1_2_9_21_1","doi-asserted-by":"publisher","DOI":"10.1145\/3770177.3770249"},{"key":"e_1_2_9_22_1","doi-asserted-by":"publisher","DOI":"10.70731\/c3q02875"},{"key":"e_1_2_9_23_1","unstructured":"Y.Wang J.Wang T.\u2010Y.Huang J.Yang andZ.Xu \u201cSTGCN\u2010LSTM for Olympic Medal Prediction: Dynamic Power Modeling and Causal Policy Optimization \u201d(2025) arXiv preprint arXiv:2501.17711."},{"key":"e_1_2_9_24_1","doi-asserted-by":"publisher","DOI":"10.3389\/fpsyg.2022.1047990"},{"key":"e_1_2_9_25_1","doi-asserted-by":"publisher","DOI":"10.1080\/23750472.2019.1583076"},{"issue":"1","key":"e_1_2_9_26_1","first-page":"37","article-title":"Predicting Olympic Medal Counts: The Effects of Economic Development on Olympic Performance","volume":"13","author":"Bian X.","year":"2005","journal-title":"Park Place Economist"},{"key":"e_1_2_9_27_1","doi-asserted-by":"publisher","DOI":"10.1145\/3760023.3760036"},{"key":"e_1_2_9_28_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10479-022-05085-5"},{"key":"e_1_2_9_29_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.aci.2017.09.005"},{"key":"e_1_2_9_30_1","doi-asserted-by":"publisher","DOI":"10.1088\/1742-6596\/1964\/4\/042085"},{"key":"e_1_2_9_31_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-981-15-9509-7_57"},{"key":"e_1_2_9_32_1","first-page":"1","article-title":"Exploring Simple, High Quality Out\u2010Of\u2010Distribution Detection With L2 Normalization","author":"Haas J.","year":"2023","journal-title":"Transactions on Machine Learning Research"},{"key":"e_1_2_9_33_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.apm.2010.09.019"},{"key":"e_1_2_9_34_1","doi-asserted-by":"publisher","DOI":"10.3389\/fgene.2019.01205"},{"key":"e_1_2_9_35_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"e_1_2_9_36_1","unstructured":"\u201c120\u2009Years of Olympic History: Athletes and Results \u201daccessed on December 2023 https:\/\/www.kaggle.com\/datasets\/heesoo37\/120\u2010years\u2010of\u2010olympic\u2010history\u2010athletes\u2010and\u2010results."}],"container-title":["Concurrency and Computation: Practice and Experience"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/cpe.70653","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/full-xml\/10.1002\/cpe.70653","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/cpe.70653","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,11]],"date-time":"2026-04-11T03:33:52Z","timestamp":1775878432000},"score":1,"resource":{"primary":{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/10.1002\/cpe.70653"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,3,19]]},"references-count":35,"journal-issue":{"issue":"7","published-print":{"date-parts":[[2026,4]]}},"alternative-id":["10.1002\/cpe.70653"],"URL":"https:\/\/doi.org\/10.1002\/cpe.70653","archive":["Portico"],"relation":{},"ISSN":["1532-0626","1532-0634"],"issn-type":[{"value":"1532-0626","type":"print"},{"value":"1532-0634","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,3,19]]},"assertion":[{"value":"2025-12-09","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2026-02-25","order":2,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2026-03-19","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}],"article-number":"e70653"}}