{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T04:11:33Z","timestamp":1760242293058,"version":"build-2065373602"},"reference-count":32,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2017,3,7]],"date-time":"2017-03-07T00:00:00Z","timestamp":1488844800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Spanish Ministry of Economics and Competitiveness","award":["AYA2014-57648-P"],"award-info":[{"award-number":["AYA2014-57648-P"]}]},{"DOI":"10.13039\/100011941","name":"Government of the Principality of Asturias","doi-asserted-by":"publisher","award":["FC-15-GRUPIN14-017"],"award-info":[{"award-number":["FC-15-GRUPIN14-017"]}],"id":[{"id":"10.13039\/100011941","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Entropy"],"abstract":"<jats:p>Adaptive optics reconstructors are needed to remove the effects of atmospheric distortion in optical systems of large telescopes. The use of reconstructors based on neural networks has been proved successful in recent times. Some of their properties require a specific characterization. A procedure, based in time series clustering algorithms, is presented to characterize the relationship between temporal structure of inputs and outputs, through analyzing the data provided by the system. This procedure is used to compare the performance of a reconstructor based in Artificial Neural Networks, with one that shows promising results, but is still in development, in order to corroborate its suitability previously to its implementation in real applications. Also, this procedure could be applied with other physical systems that also have evolution in time.<\/jats:p>","DOI":"10.3390\/e19030103","type":"journal-article","created":{"date-parts":[[2017,3,7]],"date-time":"2017-03-07T11:12:32Z","timestamp":1488885152000},"page":"103","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":17,"title":["Analysis of the Temporal Structure Evolution of Physical Systems with the Self-Organising Tree Algorithm (SOTA): Application for Validating Neural Network Systems on Adaptive Optics Data before On-Sky Implementation"],"prefix":"10.3390","volume":"19","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5260-4381","authenticated-orcid":false,"given":"Sergio","family":"Su\u00e1rez G\u00f3mez","sequence":"first","affiliation":[{"name":"Departamento de Explotaci\u00f3n y Prospecci\u00f3n de Minas, University of Oviedo, Independencia 13, 33004 Oviedo, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2038-4606","authenticated-orcid":false,"given":"Jes\u00fas","family":"Santos Rodr\u00edguez","sequence":"additional","affiliation":[{"name":"Departamento de F\u00edsica, Universidad de Oviedo, Calvo Sotelo s\/n, 33007 Oviedo, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9345-5113","authenticated-orcid":false,"given":"Francisco","family":"Iglesias Rodr\u00edguez","sequence":"additional","affiliation":[{"name":"Departamento de Administraci\u00f3n de Empresas, Universidad de Oviedo, Avenida de El Cristo s\/n, 33071 Oviedo, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Francisco","family":"De Cos Juez","sequence":"additional","affiliation":[{"name":"Departamento de Explotaci\u00f3n y Prospecci\u00f3n de Minas, University of Oviedo, Independencia 13, 33004 Oviedo, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2017,3,7]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"3539","DOI":"10.1016\/j.amc.2011.08.100","article-title":"Prediction of work-related accidents according to working conditions using support vector machines","volume":"218","author":"Lasheras","year":"2011","journal-title":"Appl. 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