{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T13:09:06Z","timestamp":1743080946338,"version":"3.40.3"},"publisher-location":"Cham","reference-count":8,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031611360"},{"type":"electronic","value":"9783031611377"}],"license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024]]},"DOI":"10.1007\/978-3-031-61137-7_29","type":"book-chapter","created":{"date-parts":[[2024,5,30]],"date-time":"2024-05-30T07:10:33Z","timestamp":1717053033000},"page":"314-322","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Autoencoder Framework for\u00a0General Forecasting"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9604-0554","authenticated-orcid":false,"given":"Du\u0161an","family":"Fister","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1260-8112","authenticated-orcid":false,"given":"C.","family":"Pel\u00e1ez-Rodr\u00edguez","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4126-8041","authenticated-orcid":false,"given":"L.","family":"Cornejo-Bueno","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4456-9886","authenticated-orcid":false,"given":"J.","family":"P\u00e9rez-Aracil","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4048-1676","authenticated-orcid":false,"given":"S.","family":"Salcedo-Sanz","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,5,31]]},"reference":[{"key":"29_CR1","doi-asserted-by":"publisher","DOI":"10.1016\/j.engappai.2023.107536","volume":"128","author":"J Donnelly","year":"2024","unstructured":"Donnelly, J., Daneshkhah, A., Abolfathi, S.: Forecasting global climate drivers using gaussian processes and convolutional autoencoders. Eng. Appl. Artif. Intell. 128, 107536 (2024)","journal-title":"Eng. Appl. Artif. Intell."},{"key":"29_CR2","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2023.110118","volume":"136","author":"D Fister","year":"2023","unstructured":"Fister, D., P\u00e9rez-Aracil, J., Pel\u00e1ez-Rodr\u00edguez, C., Del Ser, J., Salcedo-Sanz, S.: Accurate long-term air temperature prediction with machine learning models and data reduction techniques. Appl. Soft Comput. 136, 110118 (2023)","journal-title":"Appl. Soft Comput."},{"issue":"23","key":"29_CR3","doi-asserted-by":"publisher","first-page":"8931","DOI":"10.5194\/gmd-15-8931-2022","volume":"15","author":"B Gong","year":"2022","unstructured":"Gong, B., et al.: Temperature forecasting by deep learning methods. Geosci. Model Develop. 15(23), 8931\u20138956 (2022)","journal-title":"Geosci. Model Develop."},{"key":"29_CR4","unstructured":"Gr\u00f6nquist, P., et al.: Predicting weather uncertainty with deep convnets. arXiv preprint arXiv:1911.00630 (2019)"},{"key":"29_CR5","doi-asserted-by":"crossref","unstructured":"Hoeller, J., Fi\u00e9vet, R., Engelbrecht, E., Haerter, J.O.: U-net segmentation for the detection of convective cold pools from cloud and rainfall fields. J. Geophys. Res.: Atmos. 129(1), e2023JD040126 (2024)","DOI":"10.1029\/2023JD040126"},{"key":"29_CR6","doi-asserted-by":"crossref","unstructured":"Melinc, B., Zaplotnik, \u017d.: Neural-network data assimilation using variational autoencoder. arXiv preprint arXiv:2308.16073 (2023)","DOI":"10.1002\/qj.4708"},{"key":"29_CR7","doi-asserted-by":"publisher","first-page":"234","DOI":"10.1007\/978-3-319-24574-4_28","volume-title":"Medical Image Computing and Computer-Assisted Intervention \u2013 MICCAI 2015: 18th International Conference, Munich, Germany, October 5-9, 2015, Proceedings, Part III","author":"O Ronneberger","year":"2015","unstructured":"Ronneberger, O., Fischer, P., Brox, T.: U-Net: convolutional networks for biomedical image segmentation. In: Navab, N., Hornegger, J., Wells, W.M., Frangi, A.F. (eds.) Medical Image Computing and Computer-Assisted Intervention \u2013 MICCAI 2015: 18th International Conference, Munich, Germany, October 5-9, 2015, Proceedings, Part III, pp. 234\u2013241. Springer International Publishing, Cham (2015). https:\/\/doi.org\/10.1007\/978-3-319-24574-4_28"},{"key":"29_CR8","doi-asserted-by":"publisher","DOI":"10.1016\/j.envsoft.2020.104856","volume":"134","author":"M Sadeghi","year":"2020","unstructured":"Sadeghi, M., Nguyen, P., Hsu, K., Sorooshian, S.: Improving near real-time precipitation estimation using a u-net convolutional neural network and geographical information. Environ. Modell. Softw. 134, 104856 (2020)","journal-title":"Environ. Modell. Softw."}],"container-title":["Lecture Notes in Computer Science","Bioinspired Systems for Translational Applications: From Robotics to Social Engineering"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-61137-7_29","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,5,30]],"date-time":"2024-05-30T07:15:58Z","timestamp":1717053358000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-61137-7_29"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"ISBN":["9783031611360","9783031611377"],"references-count":8,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-61137-7_29","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2024]]},"assertion":[{"value":"31 May 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"IWINAC","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Work-Conference on the Interplay Between Natural and Artificial Computation","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Olh\u00e2o","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Portugal","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2024","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"31 May 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"3 June 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"10","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"iwinac2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/iwinac.eu\/iwinac.org\/iwinac2024\/index.html","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}