Претрага
41 items
-
Osnove mašinskog učenja u hidrogeologiji
Mašinsko učenje predstavlja skup metoda koje se u poslednje vreme koriste u brojnim naučnim oblastima i koje su uveliko promenile način na koji analiziramo podatke, pravimo predviđanja i rešavamo složene probleme. Poslednjih godina, mašinsko učenje se pokazalo kao moćan alat u svetu nauke, koji ima ogroman potencijal i u hidrogeologiji. Sa svojom sposobnošću da automatski uči iz ogromne količine podataka, mašinsko učenje otvara nove mogućnosti za rešavanje problema kao što su karakterizacija izdani, procena kvaliteta vode i predviđanje nivoa ...Ivan Drakulić, Dušan Polomčić, Jelena Ratković. "Osnove mašinskog učenja u hidrogeologiji" in Zapisnici srpskog geološkog društva (za 2023. godinu), Srpsko geološko društvo (2024)
-
Application of machine learning for diagnosing the operation of a deep well pump in oil production
Maja Trikić (2024)This paper will thoroughly examine how machine learning can improve the diagnosis of deep well pumps by analyzing the role and function of the pumps, dynamograms, sensor technologies, and diagnostic methods.Our analysis will provide insights into modern techniques and approaches for enhancing the performance and reliability of oil production systems, targeting cost reduction and increased operational efficiency.deep well pump, dynamograms, machine learning, diagnostics of operating coditions,Random Forest, XGBoostMaja Trikić. Application of machine learning for diagnosing the operation of a deep well pump in oil production, 2024
-
Machine learning based landslide assessment of the Belgrade metropolitan area: Pixel resolution effects and a cross-scaling concept
Improvements of Machine Learning-based landslide prediction models can be made by optimizing scale, customizing training samples to provide sets with the best examples, feature selection, etc. Herein, a novel approach, named Cross-Scaling, is proposed that includes the mixing of training and testing set resolutions. Hypothetically, training on a coarser resolution dataset and testing the model on a finer resolution should help the algorithm to better generalize ambiguous examples of landslide classes and yield fewer over/underestimations in the model. This ...Uroš Đurić, Miloš Marjanović, Zoran Radić, Biljana Abolmasov. " Machine learning based landslide assessment of the Belgrade metropolitan area: Pixel resolution effects and a cross-scaling concept" in Engineering Geology , Elsevier (2019). https://doi.org/10.1016/j.enggeo.2019.05.007
-
Integrating landslide magnitude in the susceptibility assessment of the City of Doboj, using machine learning and heuristic approach
In this work, landslide assessment of the Doboj City area was modeled by combining machine learning and heuristic tools. The machine learning part was used to map the Morphometric factor. i.e. probability of landslides based on relation between the magnitude of events and morphometric parameters: elevation, distance to streams, slope, profile curvature, and aspect. The Random Forest and Support Vector Machines algorithms were implemented in the learning protocol, which included several strategies: balancing of the training/testing set size, algorithm ...Cvjetko Sandić, Miloš Marjanović, Biljana Abolmasov, Radislav Tošić. "Integrating landslide magnitude in the susceptibility assessment of the City of Doboj, using machine learning and heuristic approach" in Journal of Maps, Taylor&Francis (2023). https://doi.org/ 10.1080/17445647.2022.2163199
-
Concepts for Improving Machine Learning Based Landslide Assessment
Miloš Marjanović, Mileva Samardžić Petrović, Biljana Abolmasov, Uroš Đurić. "Concepts for Improving Machine Learning Based Landslide Assessment" in Natural Hazards GIS-based Spatial Modeling Using Data Mining Techniques, Advances in Natural and Technological Hazards Research, volume 48, Springer Nature Switzerland AG 2019 (2019). https://doi.org/10.1007/978-3-319-73383-8_2
-
Sentiment Analysis of Serbian Old Novels
In this paper we present first study of Sentiment Analysis (SA) of Serbian novels from the 1840-1920 period. The preparation of sentiment lexicon was based on three existing lexicons: NRC, AFFIN and Bing with additional extensive corrections. The first phase of dataset refinement included filtering the word that are not found in Serbian morphological dictionary and in second automatic POS tagging and lemma were manually corrected. The polarity lexicon was extracted and transformed into ontolex-lemon and published as initial ...Ranka Stanković, Miloš Košprdić, Milica Ikonić Nešić, Tijana Radović. "Sentiment Analysis of Serbian Old Novels" in Proceedings of the 2nd Workshop on Sentiment Analysis and Linguistic Linked Data, June 2022, Marseille, France, European Language Resources Association (2022)
-
Interpretation of Trace Element Chemistry of Zircons from Bor and Cukaru Peki: Conventional Approach and Random Forest Classification
Dina Klimentyeva, Milos Velojic , Albrecht Von Quadt, Shawn Hood. "Interpretation of Trace Element Chemistry of Zircons from Bor and Cukaru Peki: Conventional Approach and Random Forest Classification" in Geosciences (2022). https://doi.org/https://doi.org/10.3390/geosciences12110396
-
Sourcing of groundwater inflows into underground mining works based on statistical modelling and artificial neural networks – the “Čukaru Peki” Cu-Au mine case study
rudničke vode, kvalitet podzemnih voda, rudnička hidrogeologija, statističko modeliranje, mašinsko učenjeNebojša Atanacković, Jana Štrbački, Sunčica Gardijan, Vladimir Živanović. "Sourcing of groundwater inflows into underground mining works based on statistical modelling and artificial neural networks – the “Čukaru Peki” Cu-Au mine case study" in IAH 2024 World Groundwater Congress - Interacting Groundwater, Davos, Švajcarska, 08-13.09.2024, Centre for Hydrogeology and Geothermics (CHYN), UNINE (2024)
-
Part of Speech Tagging for Serbian language using Natural Language Toolkit
Ranka Stanković, Boro Milovanović (2020)Dok se razvijaju složeni algoritmi za NLP (obrada prirodnog jezika), osnovni zadaci kao što je označavanje ostaju veoma važni i još uvek izazovni. NLTK (Natural Language Toolkit) je moćna Python biblioteka za razvoj programa zasnovanih na NLP-u. Pokušavamo da iskoristimo ovu biblioteku za kreiranje PoS (vrsta reči) oznake za savremeni srpski jezik. Jedanaest različitih modela je kreirano korišćenjem NLTK API-ja za označavanje. Najbolji modeli se transformišu sa Brill tagerom da bi se poboljšala tačnost. Obučili smo modele na označenom ...Ranka Stanković, Boro Milovanović. "Part of Speech Tagging for Serbian language using Natural Language Toolkit" in 7th International Conference on Electrical, Electronic and Computing Engineering IcETRAN 2020, Academic Mind, Belgrade (2020)
-
SASA Dictionary as the Gold Standard for Good Dictionary Examples for Serbian
Ranka Stanković, Branislava Šandrih, Rada Stijović, Cvetana Krstev, Duško Vitas, Aleksandra Marković (2019)У овом раду представљамо модел за избор добрих примера за речник српског језика и развој иницијалних компоненти модела. Метода која се користи заснива се на детаљној анализи различитих лексичких и синтактичких карактеристика у корпусу састављених од примера из пет дигитализованих свезака речника САНУ. Почетни скуп функција био је инспирисан сличним приступом и за друге језике. Дистрибуција карактеристика примера из овог корпуса упоређује се са карактеристиком дистрибуције узорака реченица ексцерпираних из корпуса који садрже различите текстове. Анализа је показала да ...Српски, добри примери из речника, аутоматизација израде речника, издвајање својстава, Машинско учењеRanka Stanković, Branislava Šandrih, Rada Stijović, Cvetana Krstev, Duško Vitas, Aleksandra Marković. "SASA Dictionary as the Gold Standard for Good Dictionary Examples for Serbian" in Electronic lexicography in the 21st century. Proceedings of the eLex 2019 conference , Lexical Computing CZ, s.r.o. (2019)
-
A Mathematical Learning Environment Based on Serbian Language Resources
In recent years, in line with ever growing usage of Information technology, the learning environments are changing. The amount of available learning materials in various forms has increased. These new environments demand comprehensive learning systems, which enable management of the learning corpus with special attention paid to relevant lexical resources. In this paper we present the concept of a Mathematical Learning Environment in Serbian (MLES), which is based on a corpus of mathematical materials and various lexical resources, enabling ...Radojičić Marija, Obradović Ivan, Stanković Ranka, Utvić Miloć, Kaplar Sebastijan. "A Mathematical Learning Environment Based on Serbian Language Resources" in Proceedings of the 7th International Scientific Conference Technics and Informatics in Education, Faculty of Technical Sciences, Čačak (2018)
-
Evaluating the deep learning software tools for large-scale enterprises using a novel TODIFFA-MCDM framework
Zoran Gligorić, Ömer Faruk Görçün, Miloš Gligorić, Dragan Pamucar, Vladimir Simić, Hande Küçükönder (2024)duboko učenje, industrije velikih razmera, MAXC (maksimum kriterijuma), TODIFFA (totalni diferencijal alternative), izbor softvera za dubinsko učenjeZoran Gligorić, Ömer Faruk Görçün, Miloš Gligorić, Dragan Pamucar, Vladimir Simić, Hande Küçükönder. "Evaluating the deep learning software tools for large-scale enterprises using a novel TODIFFA-MCDM framework" in Journal of King Saud University - Computer and Information Sciences, Springer Science and Business Media LLC (2024). https://doi.org/10.1016/j.jksuci.2024.102079
-
Primena klasterizacije metodom K-srednjih vrednosti za ispitivanje hidrohemijskog diverziteta podzemnih voda na lokaciji Vrnjačke Banje
Klasterizacija metodom k-srednjih vrednosti koristi se za razvrstavanje podataka u homogene grupe, tj. klastere, na osnovu odabranih varijabli i unapred zadatog broja klastera. Algoritam iterativnim postupkom određuje centre klastera i dodeljuje uzorke u klastere čijem su centru najbliži. Ovaj postupak pogodan je za raščlanjivanje i, samim tim, pojednostavljivanje obimnih skupova hidrohemijskih podataka, što je pokazano na primeru termo-mineralnih voda sa šireg područja Vrnjačke Banje. Pored same klasifikacije, opisana metoda pruža mogućnost provere hipoteza o strukturi podataka, npr. o postojanju ...Jana Štrbački, Vladimir Živanović, Nebojša Atanacković, Snežana Kretić. "Primena klasterizacije metodom K-srednjih vrednosti za ispitivanje hidrohemijskog diverziteta podzemnih voda na lokaciji Vrnjačke Banje" in XVII Srpski simpozijum o hidrogeologiji sa međunarodnim učešćem , Pirot, Srbija, 02-06. oktobar 2024, Beograd : Univerzitet u Beogradu - Rudarsko-geološki fakultet (2024). https://doi.org/10.5281/zenodo.13739553
-
Creating an environment for free education and technology enhanced learning
Radojičić Marija, Obradović Ivan, Tatar Saša, Linzalone Roberto, Schiuma Giovanni, Carlucci Daniela (2014)Radojičić Marija, Obradović Ivan, Tatar Saša, Linzalone Roberto, Schiuma Giovanni, Carlucci Daniela. "Creating an environment for free education and technology enhanced learning" in Proc. of the Fifth International Conference on e-learning (eLearning-2014), 22-23 September, Belgrade, Serbia, Belgrade:Metropolitan University (2014): 44-48
-
Conventional and machine learning methods for landslide assessment in GIS
Marjanović Miloš (2014)Marjanović Miloš. Conventional and machine learning methods for landslide assessment in GIS, Olomouc, Cyech Republic:Palacký University in Olomouc"", 2014
-
Building Terminological Resources in an e-Learning Environment
Ranka Stanković, Ivan Obradović, Olivera Kitanović, Ljiljana Kolonja. "Building Terminological Resources in an e-Learning Environment" in Proceedings of the Third International Conference on e-Learning, eLearning-2012, September 2012, Belgrade, Serbia, Belgrade : Belgrade Metropolitan University (2012)
-
An aproach to Implementation of blended learning in a university setting
Ivan Obradović, Ranka Stanković, Olivera Kitanović, Jelena Prodanović . "An aproach to Implementation of blended learning in a university setting" in Proceedings of the Second International Conference on e-Learning, eLearning 2011, September 2011, Belgrade, Serbia, Belgrade : Belgrade Metropolitan University (2011)
-
Formative evaluation of e-learning projects with the logical framework approach
Roberto Linzalone, Giovani Schiuma, Ivan Obradović, Ranka Stanković. "Formative evaluation of e-learning projects with the logical framework approach" in The Sixth International Conference on e-Learning (eLearning-2015), September 2015, Belgrade, Serbia, Belgrade Metropolitan Univesity (2015)
-
Building learning capacity by blending different sources of knowledge
Ivan Obradović, Ranka Stanković, Olivera Kitanović, Dalibor Vorkapić. "Building learning capacity by blending different sources of knowledge" in International Journal of Learning and Intellectual Capital (2016). https://doi.org/10.1504/IJLIC.2016.075698
-
Landslide susceptibility assessment using SVM machine learning algorithm
Marjanović Miloš, Kovačević Miloš, Bajat Branislav, Voženilek Vít. "Landslide susceptibility assessment using SVM machine learning algorithm" in Engineering Geology 123 no. 3, Amsterdam, Netherlands:Elsevier (2011): 225-234. https://doi.org/10.1016/j.enggeo.2011.09.006