{"?xml":{"@version":"1.0"},"edm:RDF":{"@xmlns:dc":"http://purl.org/dc/elements/1.1/","@xmlns:edm":"http://www.europeana.eu/schemas/edm/","@xmlns:wgs84_pos":"http://www.w3.org/2003/01/geo/wgs84_pos","@xmlns:foaf":"http://xmlns.com/foaf/0.1/","@xmlns:rdaGr2":"http://rdvocab.info/ElementsGr2","@xmlns:oai":"http://www.openarchives.org/OAI/2.0/","@xmlns:owl":"http://www.w3.org/2002/07/owl#","@xmlns:rdf":"http://www.w3.org/1999/02/22-rdf-syntax-ns#","@xmlns:ore":"http://www.openarchives.org/ore/terms/","@xmlns:skos":"http://www.w3.org/2004/02/skos/core#","@xmlns:dcterms":"http://purl.org/dc/terms/","edm:WebResource":[{"@rdf:about":"http://www.dlib.si/stream/URN:NBN:SI:doc-W893RNDD/624b64ee-14d0-423e-afa1-7f12b1c49792/PDF","dcterms:extent":"239 KB"},{"@rdf:about":"http://www.dlib.si/stream/URN:NBN:SI:doc-W893RNDD/988dd1bf-dac9-4bba-b878-1d1282548385/TEXT","dcterms:extent":"0 KB"}],"edm:TimeSpan":{"@rdf:about":"1999-2025","edm:begin":{"@xml:lang":"en","#text":"1999"},"edm:end":{"@xml:lang":"en","#text":"2025"}},"edm:ProvidedCHO":{"@rdf:about":"URN:NBN:SI:doc-W893RNDD","dcterms:isPartOf":[{"@rdf:resource":"https://www.dlib.si/details/URN:NBN:SI:spr-WP8SPN4L"},{"@xml:lang":"sl","#text":"Acta hydrotechnica"}],"dcterms:issued":"2002","dc:creator":["Atanasova, Nataša","Kompare, Boris"],"dc:format":[{"@xml:lang":"sl","#text":"letnik:20"},{"@xml:lang":"sl","#text":"številka:33"},{"@xml:lang":"sl","#text":"Str. 351-370"}],"dc:identifier":["ISSN:1581-0267","COBISSID_HOST:1853025","URN:URN:NBN:SI:doc-W893RNDD"],"dc:language":"sl","dc:publisher":{"@xml:lang":"sl","#text":"Fakulteta za gradbeništvo in geodezijo"},"dc:subject":[{"@xml:lang":"sl","#text":"čistilne naprave"},{"@xml:lang":"en","#text":"decision trees"},{"@xml:lang":"en","#text":"machine learning"},{"@xml:lang":"sl","#text":"modeliranje"},{"@xml:lang":"en","#text":"modelling"},{"@xml:lang":"sl","#text":"odločitvena drevesa"},{"@xml:lang":"sl","#text":"odpadne vode"},{"@xml:lang":"sl","#text":"strojno učenje"},{"@xml:lang":"en","#text":"wastewater"},{"@xml:lang":"en","#text":"wastewater treatment plant"}],"dcterms:temporal":{"@rdf:resource":"1999-2025"},"dc:title":{"@xml:lang":"sl","#text":"Uporaba odločitvenih dreves pri modeliranju čistilne naprave za odpadno vodo| The use of decision trees in the modelling of a wastewater treatment plant|"},"dc:description":[{"@xml:lang":"sl","#text":"Wastewater treatment plants (WWTP) are dynamic and complex systems, the management of which can be improved by different approaches to modelling and predicting their operation. Machine learning tools (decision trees) were used to build useful prediction models for wastewater treatment plant operation. The data base used for building the models is composed of measured quantitative as well as qualitative data on the WWTP. We were also provided with a microbiological analysis. The data are presented as a one-day situationof the plant operation. So far, classification of the data was made using the Linneo+ methodology. We extended the knowledge gained by classification by analyzing the classified data and constructing useful modelsthat predict WWTP operation from inflow data. The WEKA program package, which includes most of the popular machine learning algorithms, was used for constructing the models"},{"@xml:lang":"sl","#text":"Čistilne naprave (ČN) za odpadno vodo so dinamični in kompleksni sistemi, katerih vodenje lahko izboljšamo z različnimi pristopi k modeliranju in napovedovanju delovanja ČN. V nalogi smo poskušali zgraditi uporabne modele za napoved delovanja čistilne naprave z orodji strojnega učenja, točneje z odločitvenimi drevesi. Podatkovna baza, iz katere smo modele gradili, je sestavljena iz enodnevnih povprečnih merjenih podatkov na ČN. Poleg kvantitativnih podatkov je baza sestavljena iz številnih kvalitativnih ocen, kakor tudi iz obsežne mikrobiološke analize. Dosedanja obdelava podatkov je obsegala klasifikacijo podatkov z Linneo+ postopkom. Temu smo dodali izgradnjo preprostih, a dovolj natančnih modelov, ki predvidevajo funkcionalno stanje ČN na podlagi merjenih (kvantitativnih) vhodnih podatkov. Za izgradnjo modelov smo uporabili programski paket WEKA, ki ima vgrajeno večino popularnih algoritmov strojnega učenja"}],"edm:type":"TEXT","dc:type":[{"@xml:lang":"sl","#text":"znanstveno časopisje"},{"@xml:lang":"en","#text":"journals"},{"@rdf:resource":"http://www.wikidata.org/entity/Q361785"}]},"ore:Aggregation":{"@rdf:about":"http://www.dlib.si/?URN=URN:NBN:SI:doc-W893RNDD","edm:aggregatedCHO":{"@rdf:resource":"URN:NBN:SI:doc-W893RNDD"},"edm:isShownBy":{"@rdf:resource":"http://www.dlib.si/stream/URN:NBN:SI:doc-W893RNDD/624b64ee-14d0-423e-afa1-7f12b1c49792/PDF"},"edm:rights":{"@rdf:resource":"http://creativecommons.org/licenses/by-nc-sa/4.0/"},"edm:provider":"Slovenian National E-content Aggregator","edm:intermediateProvider":{"@xml:lang":"en","#text":"National and University Library of Slovenia"},"edm:dataProvider":{"@xml:lang":"sl","#text":"Univerza v Ljubljani, Fakulteta za gradbeništvo in geodezijo"},"edm:object":{"@rdf:resource":"http://www.dlib.si/streamdb/URN:NBN:SI:doc-W893RNDD/maxi/edm"},"edm:isShownAt":{"@rdf:resource":"http://www.dlib.si/details/URN:NBN:SI:doc-W893RNDD"}}}}