https://hdl.handle.net/10259/4164 Fri, 17 Apr 2026 11:57:57 GMT 2026-04-17T11:57:57Z https://hdl.handle.net/10259/7267 A hybrid intelligent system for the analysis of atmospheric pollution: a case study in two European regions Arroyo Puente, Ángel; Herrero Cosío, Álvaro; Corchado, Emilio; Tricio Gómez, Verónica 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. Fri, 01 Dec 2017 00:00:00 GMT https://hdl.handle.net/10259/7267 2017-12-01T00:00:00Z https://hdl.handle.net/10259/7261 Neural Models for Imputation of Missing Ozone Data in Air-Quality Datasets Arroyo Puente, Ángel; Herrero Cosío, Álvaro; Tricio Gómez, Verónica; Corchado, Emilio; Woźniak, Michał Ozone is one of the pollutants with most negative efects on human health and in general on the biosphere. Many data-acquisition networks collect data about ozone values in both urban and background areas. Usually, these data are incomplete or corrupt and the imputation of the missing values is a priority in order to obtain complete datasets, solving the uncertainty and vagueness of existing problems to manage complexity. In the present paper, multiple-regression techniques and Artifcial Neural Network models are applied to approximate the absent ozone values from fve explanatory variables containing air-quality information. To compare the diferent imputation methods, real-life data from six data-acquisition stations from the region of Castilla y Leon (Spain) are gathered ´ in diferent ways and then analyzed. Te results obtained in the estimation of the missing values by applying these techniques and models are compared, analyzing the possible causes of the given response. Mon, 01 Jan 2018 00:00:00 GMT https://hdl.handle.net/10259/7261 2018-01-01T00:00:00Z https://hdl.handle.net/10259/7255 Self-Organizing Maps to Validate Anti-Pollution Policies Arroyo Puente, Ángel; Cambra Baseca, Carlos; Herrero Cosío, Álvaro; Tricio Gómez, Verónica; Corchado, Emilio This study presents the application of self-organizing maps to air-quality data in order to analyze episodes of high pollution in Madrid (Spain’s capital city). The goal of this work is to explore the dataset and then compare several scenarios with similar atmospheric conditions (periods of high Nitrogen dioxide concentration): some of them when no actions were taken and some when traffic restrictions were imposed. The levels of main pollutants, recorded at these stations for eleven days at four different times from 2015 to 2018, are analyzed in order to determine the effectiveness of the anti-pollution measures. The visualization of trajectories on the self-organizing map let us clearly see the evolution of pollution levels and consequently evaluate the effectiveness of the taken measures, after and during the protocol activation time. Thu, 01 Aug 2019 00:00:00 GMT https://hdl.handle.net/10259/7255 2019-08-01T00:00:00Z https://hdl.handle.net/10259/6356 High-resolution late Middle Pleistocene paleoclimatic record from the Galería Complex, Atapuerca archaeological site, Spain - An environmental magnetic approach Bógalo Román, Mª Felicidad; Bradák, Balázs; Villalaín Santamaria, Juan José; Calvo Rathert, Manuel; González Martín, Manuel Iván; Heller, F.; Ortega Martínez, Ana Isabel; Parés Casanova, Josep M. The Galería Complex is a cave sediment succession at the Atapuerca paleoanthropological site (Burgos, Spain) that offers detailed environmental information about the late Middle Pleistocene, especially the period between marine oxygen isotope stages MIS10 and MIS7. Previous studies have reconstructed the chronology and detailed the environmental development of this key succession. We introduce rock magnetic climate proxies from the sedimentary units of the Galería succession that we correlate with the global climate record as represented by the marine oxygen isotope record. The cave sediment sequence consists of five infilling phases, four of which were sampled at high resolution across a 5 m thick composite profile. We propose a novel goethite climate proxy along with a frequently used ultrafine ferrimagnetic mineral proxy for paleoclimate reconstruction and detailed chronostratigraphic correlation with isotope stages and substages MIS10/MIS10-9, MIS9e-a and MIS8. The proxies reveal new paleoenvironmental information about paleoprecipitation and indicate that MIS9e was a humid (∼650 mm/year maximum annual precipitation) and intense interglacial in northern Spain that declined in steps into the globally weak glacial stage MIS8. MIS8 consisted of drier periods with 430–510 mm/year annual precipitation and at least one humid substage (600 mm/year). Fri, 01 Jan 2021 00:00:00 GMT https://hdl.handle.net/10259/6356 2021-01-01T00:00:00Z