prikaz prve stranice dokumenta Geografski ponderirana neuronska mreža
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undergraduate thesis
Geografski ponderirana neuronska mreža
2022. urn:nbn:hr:168:699447
Sever, Matija
University of Zagreb
Faculty of Electrical Engineering and Computing

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Sever, M. (2022). Geografski ponderirana neuronska mreža (Undergraduate thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:699447

Sever, Matija. "Geografski ponderirana neuronska mreža." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2022. https://urn.nsk.hr/urn:nbn:hr:168:699447

Sever, Matija. "Geografski ponderirana neuronska mreža." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2022. https://urn.nsk.hr/urn:nbn:hr:168:699447

Sever, M. (2022). 'Geografski ponderirana neuronska mreža', Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 14 May 2024, https://urn.nsk.hr/urn:nbn:hr:168:699447

Sever M. Geografski ponderirana neuronska mreža [Undergraduate thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2022 [cited 2024 May 14] Available at: https://urn.nsk.hr/urn:nbn:hr:168:699447

M. Sever, "Geografski ponderirana neuronska mreža", Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2022. Available at: https://urn.nsk.hr/urn:nbn:hr:168:699447

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Metadata
TitleGeografski ponderirana neuronska mreža
Title (english)A geographically weighted neural network
AuthorMatija Sever
MentorMartina Antonić (mentor)
Committee memberMartina Antonić (predsjednik povjerenstva)
Committee memberJosip Marić (član povjerenstva)
Committee memberMarko Pavelić (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2022-07-04, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
Tema rada je „Geografski ponderirana neuronska mreža“. U radu se naglašava problem prostorne heterogenosti te njegovo rješavanje. Analizira se geografski ponderirana regresija te se ukazuje na njezine nedostatke kod predviđanja heterogenog prostora. Predstavlja se i opisuje rješenje za geografski ponderiranu regresiju pomoću geografski ponderirane neuronske mreže koje su implementirane u programskom jeziku Python. Razlika između geografski ponderirane regresije i geografski ponderirane neuronske mreže prikazana je njihovim testiranjem na četiri skupa umjetnih podataka različite prostorne heterogenosti i vizualizacijom njihovih rezultata.
Abstract (english)
The topic of the paper is "Geographically weighted neural network". The paper emphasizes the problem of spatial heterogeneity and its solution. Geographically weighted regression is analyzed and its shortcomings in predicting heterogeneous space are pointed out. A solution for geographically weighted regression using geographically weighted neural networks implemented in the Python programming language is presented and described. The difference between geographically weighted regression and geographically weighted neural network is shown by testing them on four sets of artificial data of different spatial heterogeneity and visualizing their results.
Languagecroatian
URN:NBNurn:nbn:hr:168:699447
Study programmeTitle: Computing
Study programme type: university
Study level: undergraduate
Academic / professional title: sveučilišni/a prvostupnik/ prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka računarstva (sveučilišni/a prvostupnik/ prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka računarstva)
Type of resourceText
File originBorn digital
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Created on2023-01-15 11:12:28