{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,24]],"date-time":"2025-09-24T10:22:08Z","timestamp":1758709328357},"reference-count":36,"publisher":"Oxford University Press (OUP)","issue":"6","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2017,12,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>The combined application of several soft-computing and statistical techniques is proposed for the characterization of atmospheric conditions in two European regions: Madrid (Spain) and Prague (Czech Republic). The resulting Hybrid Artificial Intelligence System (HAIS) combines projection models for dimensionality reduction and clustering, combining neural and fuzzy paradigms, in a decision support tool. In present article, this proposed HAIS is applied to analyse the air quality in these two geographical regions and get a better understanding of its circumstances and evolution. To do so, real-life data from six data-acquisition stations are analysed. The main pollutants recorded at these stations between 2007 and 2014, their geographical locations and seasonal changes are all studied, in a research that shows how such factors determine variations in air-borne pollutants. Furthermore, neural projections of the clustering results from data on atmospheric pollution are studied.<\/jats:p>","DOI":"10.1093\/jigpal\/jzx050","type":"journal-article","created":{"date-parts":[[2017,10,13]],"date-time":"2017-10-13T15:12:47Z","timestamp":1507907567000},"page":"915-937","source":"Crossref","is-referenced-by-count":5,"title":["A hybrid intelligent system for the analysis of atmospheric pollution: a case study in two European regions"],"prefix":"10.1093","volume":"25","author":[{"given":"\u00c1ngel","family":"Arroyo","sequence":"first","affiliation":[{"name":"Department of Civil Engineering, University of Burgos, Burgos, Spain."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"\u00c1lvaro","family":"Herrero","sequence":"additional","affiliation":[{"name":"Department of Civil Engineering, University of Burgos, Burgos, Spain."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Emilio","family":"Corchado","sequence":"additional","affiliation":[{"name":"Departamento de Inform\u00e1tica y Autom\u00e1tica, University of Salamanca, Salamanca, Spain."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ver\u00f3nica","family":"Tricio","sequence":"additional","affiliation":[{"name":"Department of Physics, University of Burgos, Burgos, Spain."}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2017,11,2]]},"reference":[{"key":"2020021403110393200_B1","doi-asserted-by":"crossref","first-page":"433","DOI":"10.1002\/wics.101","article-title":"Principal component analysis.","volume":"2","author":"Abdi","year":"2010","journal-title":"Wiley Interdisciplinary Reviews: Computational Statistics"},{"key":"2020021403110393200_B2","doi-asserted-by":"crossref","first-page":"767","DOI":"10.1007\/978-3-642-04394-9_94","article-title":"Atmospheric pollution analysis by unsupervised learning.","volume":"5788","author":"Arroyo","year":"2009","journal-title":"Intelligent Data Engineering and Automated Learning - 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