Please use this identifier to cite or link to this item:
http://hdl.handle.net/10553/47152
DC Field | Value | Language |
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dc.contributor.author | Suárez Araujo, Carmen Paz | en_US |
dc.contributor.author | García Báez, Patricio | en_US |
dc.contributor.author | Sánchez Rodríguez, Álvaro | en_US |
dc.contributor.author | Santana Rodríguez, José Juan | en_US |
dc.date.accessioned | 2018-11-23T11:15:18Z | - |
dc.date.available | 2018-11-23T11:15:18Z | - |
dc.date.issued | 2009 | en_US |
dc.identifier.issn | 1618-2642 | en_US |
dc.identifier.uri | http://hdl.handle.net/10553/47152 | - |
dc.description.abstract | In this paper, we approach, using neural computation and ensemble systems, a pattern classification problem in fluorescence spectrometry, the resolution of difficult multi-fungicide mixtures (overlapping), specifically the benzimidazole fungicides, benomyl, carbendazim, thiabendazole and fuberidazole. These fungicides are compounds of an important environmental interest. Because of this, from an analytical point of view, it is interesting to develop sensitive, selective and simple methods for their determination. Fluorescence spectrometry has proven to be a sensitive and selective technique for determination of many compounds of environmental interest, but in some cases it is not enough. HUMANN is a hierarchical, unsupervised, modular, adaptive neural net with high biological plausibility, which has shown to be suitable for identification of these fungicides and organochlorinated compounds of environmental interest. We propose two modular artificial intelligent systems, with a structure of pre-processing and processing stage, a multi-input HUMANN-based system, using multi-fluorescence spectra as input to the system, and a HUMANN-ensemble system. We analyze the optimal configuration of inputs and the ensemble in order to obtain better results. We study such figures as precision and sensitivity of the method. Our proposal is a smart, flexible and effective complementary method, which allows reducing the analytical and/or computational complexity of the analysis. | en_US |
dc.language | eng | en_US |
dc.relation.ispartof | Analytical and Bioanalytical Chemistry | en_US |
dc.source | Analytical and Bioanalytical Chemistry [ISSN 1618-2642], v. 394 (4), p. 1059-1072 | en_US |
dc.subject | 120304 Inteligencia artificial | en_US |
dc.subject | 3308 Ingeniería y tecnología del medio ambiente | en_US |
dc.subject.other | Benzimidazole fungicides | en_US |
dc.subject.other | Ensemble system | en_US |
dc.subject.other | Environment | en_US |
dc.subject.other | Fluorescence spectrometry | en_US |
dc.subject.other | HUMANN | en_US |
dc.subject.other | Unsupervised artificial neural network | en_US |
dc.title | HUMANN-based system to identify benzimidazole fungicides using multi-synchronous fluorescence spectra: an ensemble approach | en_US |
dc.type | info:eu-repo/semantics/Article | es |
dc.type | Article | es |
dc.relation.conference | 13th International Symposium on Luminescence Spectrometry | |
dc.identifier.doi | 10.1007/s00216-009-2654-7 | |
dc.identifier.scopus | 67349156664 | - |
dc.identifier.isi | 000266160400016 | - |
dc.contributor.authorscopusid | 6603605708 | - |
dc.contributor.authorscopusid | 6506952458 | - |
dc.contributor.authorscopusid | 26039375100 | - |
dc.contributor.authorscopusid | 56248783900 | - |
dc.identifier.eissn | 1618-2650 | - |
dc.description.lastpage | 1072 | - |
dc.identifier.issue | 4 | - |
dc.description.firstpage | 1059 | - |
dc.relation.volume | 394 | - |
dc.investigacion | Ingeniería y Arquitectura | en_US |
dc.type2 | Artículo | en_US |
dc.contributor.daisngid | 1776211 | |
dc.contributor.daisngid | 2362390 | |
dc.contributor.daisngid | 6474544 | |
dc.contributor.daisngid | 13402121 | |
dc.utils.revision | Sí | en_US |
dc.contributor.wosstandard | WOS:Araujo, CPS | |
dc.contributor.wosstandard | WOS:Baez, PG | |
dc.contributor.wosstandard | WOS:Rodriguez, AS | |
dc.contributor.wosstandard | WOS:Rodriguez, JJS | |
dc.date.coverdate | Junio 2009 | |
dc.identifier.conferenceid | events120672 | |
dc.identifier.ulpgc | Sí | es |
dc.description.jcr | 3,48 | |
dc.description.jcrq | Q1 | |
dc.description.scie | SCIE | |
item.grantfulltext | none | - |
item.fulltext | Sin texto completo | - |
crisitem.author.dept | GIR IUCES: Computación inteligente, percepción y big data | - |
crisitem.author.dept | IU de Cibernética, Empresa y Sociedad (IUCES) | - |
crisitem.author.dept | Departamento de Informática y Sistemas | - |
crisitem.author.dept | GIR IUCES: Computación inteligente, percepción y big data | - |
crisitem.author.dept | IU de Cibernética, Empresa y Sociedad (IUCES) | - |
crisitem.author.dept | GIR Energía, Corrosión, Residuos y Agua | - |
crisitem.author.dept | Departamento de Ingeniería de Procesos | - |
crisitem.author.orcid | 0000-0002-8826-0899 | - |
crisitem.author.orcid | 0000-0002-9973-5319 | - |
crisitem.author.orcid | 0000-0002-3030-2195 | - |
crisitem.author.parentorg | IU de Cibernética, Empresa y Sociedad (IUCES) | - |
crisitem.author.parentorg | IU de Cibernética, Empresa y Sociedad (IUCES) | - |
crisitem.author.parentorg | Departamento de Ingeniería Electrónica y Automática | - |
crisitem.author.fullName | Suárez Araujo, Carmen Paz | - |
crisitem.author.fullName | García Baez, Patricio | - |
crisitem.author.fullName | Santana Rodríguez, Juan José | - |
crisitem.event.eventsstartdate | 07-09-2008 | - |
crisitem.event.eventsenddate | 11-09-2008 | - |
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