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| Ultima descărcare din IBN: 2023-06-14 07:34 |
 SM ISO690:2012PENTIUC, Stefan-Gheorghe, BOBRIC, Elena Crenguța, BILIUS, Laura-Bianca. Analysis with Unsupervised Learning Based Techniques of Load Factor Profiles and Hyperspectral Images. In: Electronics, Communications and Computing, Ed. 12, 20-21 octombrie 2022, Chişinău. Chișinău: Tehnica-UTM, 2023, Editia 12, pp. 136-139. DOI: https://doi.org/10.52326/ic-ecco.2022/SEC.05 |
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| Electronics, Communications and Computing Editia 12, 2023 |
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Conferința "Electronics, Communications and Computing" 12, Chişinău, Moldova, 20-21 octombrie 2022 | ||||||
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| DOI:https://doi.org/10.52326/ic-ecco.2022/SEC.05 | ||||||
| Pag. 136-139 | ||||||
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The problem of obtaining an optimal partition consistent with a series of partitions resulting from the application of various clustering algorithms is NP complete. A heuristic method based on the concepts of central partition and strong patterns developed by Edwin Diday [3] is proposed. It is presented the experience regarding the use of analysis techniques based on unsupervised learning methods of load factor profiles and hyperspectral images. |
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| Cuvinte-cheie machine learning, unsupervised learning, Clustering algorithms, load factor profiles, hyperspectral images |
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Google Scholar Export
<meta name="citation_title" content="Analysis with Unsupervised Learning Based Techniques of Load Factor Profiles and Hyperspectral Images"> <meta name="citation_author" content="Pentiuc Stefan-Gheorghe"> <meta name="citation_author" content="Bobric Elena Crenguța"> <meta name="citation_author" content="Bilius Laura-Bianca"> <meta name="citation_publication_date" content="2023"> <meta name="citation_collection_title" content="Electronics, Communications and Computing"> <meta name="citation_volume" content="Editia 12"> <meta name="citation_firstpage" content="136"> <meta name="citation_lastpage" content="139"> <meta name="citation_pdf_url" content="https://ibn.idsi.md/sites/default/files/imag_file/136-139_47.pdf">
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