{"?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-380RJAN2/bd8ab641-9859-4c8a-bf15-83a1540f8cef/PDF","dcterms:extent":"512 KB"},{"@rdf:about":"http://www.dlib.si/stream/URN:NBN:SI:doc-380RJAN2/1c229a0a-7e8c-4261-a984-7b8d2da02c9c/TEXT","dcterms:extent":"62 KB"}],"edm:TimeSpan":{"@rdf:about":"2015-2025","edm:begin":{"@xml:lang":"en","#text":"2015"},"edm:end":{"@xml:lang":"en","#text":"2025"}},"edm:ProvidedCHO":{"@rdf:about":"URN:NBN:SI:doc-380RJAN2","dcterms:isPartOf":[{"@rdf:resource":"https://www.dlib.si/details/URN:NBN:SI:spr-M1DCQYMN"},{"@xml:lang":"sl","#text":"Medicine, law & society"}],"dcterms:issued":"2025","dc:creator":"Sharma, Mohit","dc:format":[{"@xml:lang":"sl","#text":"številka:1"},{"@xml:lang":"sl","#text":"letnik:18"},{"@xml:lang":"sl","#text":"str. 109-131"}],"dc:identifier":["DOI:10.18690/mls.18.1.109-132.2025","ISSN:2463-7955","COBISSID_HOST:246831363","URN:URN:NBN:SI:doc-380RJAN2"],"dc:language":["en","sl"],"dc:publisher":{"@xml:lang":"sl","#text":"University of Maribor Press"},"dc:subject":[{"@xml:lang":"en","#text":"adaptation"},{"@xml:lang":"en","#text":"artificial intelligence"},{"@xml:lang":"en","#text":"electricity generation"},{"@xml:lang":"en","#text":"global warming"},{"@xml:lang":"en","#text":"mitigation"},{"@xml:lang":"en","#text":"power industry"}],"dcterms:temporal":{"@rdf:resource":"2015-2025"},"dc:title":{"@xml:lang":"sl","#text":"Artificial intelligence application through electric power and climate change|"},"dc:description":[{"@xml:lang":"sl","#text":"Assessing and directing the implications of artificial intelligence (AI) and machine learning (ML) continues to be embedded in our daily lives and involves a united effort across academics, policy, and industry with ambiguity for impacting the present and the future. AI has the potential to improve outcomes, boost productivity, and improve the precision and effectiveness of the numerous facets of society that depend on probabilities and forecasts. In summary, its applications with the greatest potential might arise from those exceptionally complicated technological challenges that lie beyond the reach of human capability rather than from uses that impact civil freedoms and the social fabric of our society. One such complicated issue is climate change, which calls for significant adjustments to the building, energy, transportation, and agricultural sectors. In order to provide more accurate forecasts of impending weather phenomena, particularly extreme events, it can also expand on the discoveries made on climate links. The article critically examines the growing application of artificial intelligence through the Electric Power Sector in India"},{"@xml:lang":"sl","#text":"Ocenjevanje in usmerjanje posledic umetne inteligence (UI) in strojnega učenja (SU) ostaja prisotno v našem vsakdanjem življenju in vključuje skupna prizadevanja akademikov, politikov in industrije z nedvoumnim vplivom na sedanjost in prihodnost. UI ima sposobnost izboljšati rezultate, povečati produktivnost ter izboljšati natančnost in učinkovitost številnih plati družbe, ki so odvisne od verjetnosti in napovedi. V povzetku, njena uporabnost z največjim potencialom bi se lahko pokazala pri tistih izjemno zapletenih tehnoloških izzivih, ki so zunaj dosega človeških zmožnosti, in ne pri takšnih uporabah, ki vplivajo na civilne svoboščine in socialno strukturo naše družbe. Eden izmed takih zapletenih problemov so denimo podnebne spremembe, ki zahtevajo znatne prilagoditve v gradbenem, energetskem, prometnem in kmetijskem sektorju. Da bi zagotovili natančnejše napovedi prihajajočih vremenskih pojavov, zlasti ekstremnih razmer, lahko tudi razširi odkritja o podnebnih povezavah. Članek kritično obravnava vse večjo uporabo umetne inteligence prek sektorja električne energije v Indiji"}],"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-380RJAN2","edm:aggregatedCHO":{"@rdf:resource":"URN:NBN:SI:doc-380RJAN2"},"edm:isShownBy":{"@rdf:resource":"http://www.dlib.si/stream/URN:NBN:SI:doc-380RJAN2/bd8ab641-9859-4c8a-bf15-83a1540f8cef/PDF"},"edm:rights":{"@rdf:resource":"http://creativecommons.org/licenses/by/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 Mariboru, Pravna fakulteta"},"edm:object":{"@rdf:resource":"http://www.dlib.si/streamdb/URN:NBN:SI:doc-380RJAN2/maxi/edm"},"edm:isShownAt":{"@rdf:resource":"http://www.dlib.si/details/URN:NBN:SI:doc-380RJAN2"}}}}