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Title:Nevronski model rezalnih sil za proces frezanja : magistrsko delo
Authors:ID Žurman, Uroš (Author)
ID Hace, Aleš (Mentor) More about this mentor... New window
ID Župerl, Uroš (Mentor) More about this mentor... New window
Files:.pdf MAG_Zurman_Uros_2022.pdf (2,37 MB)
MD5: C8FF63EBDBDB9E08CBCDA43CFCEDBECF
 
.zip MAG_Zurman_Uros_2022.zip (123,97 KB)
MD5: F85849CFF5951FD2F803B6E99B534C6E
 
Language:Slovenian
Work type:Master's thesis/paper
Typology:2.09 - Master's Thesis
Organization:FERI - Faculty of Electrical Engineering and Computer Science
Abstract:V magistrski nalogi so opisani modeli za napovedovanje rezalnih sil in principe delovanja nevronskih mrež. V osrednjem delu so predstavljeni trije umetni nevronski modeli za napovedovanje rezalne sile. Za primerjavo je bil narejen statistični model linearne regresije za napovedovanje rezalne sile. Nevronski modeli so bili narejeni s programom MATLAB, model linearne regresije pa z Microsoft Excel. Na koncu so predstavljeni rezultati treh modelov nevronske mreže in statističnega modela linearne regresije.
Keywords:frezanje, umetna nevronska mreža, regresijska analiza, rezalne sile
Place of publishing:Maribor
Place of performance:Maribor
Publisher:[U. Žurman]
Year of publishing:2022
Number of pages:1 spletni vir (1 datoteka PDF (X, 42 f.))
PID:20.500.12556/DKUM-83112 New window
UDC:004.8.032.26:621.914(043.2)
COBISS.SI-ID:143716611 New window
Publication date in DKUM:26.10.2022
Views:774
Downloads:76
Metadata:XML DC-XML DC-RDF
Categories:KTFMB - FERI
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Licences

License:CC BY 4.0, Creative Commons Attribution 4.0 International
Link:http://creativecommons.org/licenses/by/4.0/
Description:This is the standard Creative Commons license that gives others maximum freedom to do what they want with the work as long as they credit the author.
Licensing start date:19.09.2022

Secondary language

Language:English
Title:Artificial neural network based cutting force model for milling process
Abstract:The master's thesis describes models for predicting cutting forces and the principles of neural networks. In the central part, three artificial neural models for predicting the cutting force are presented. For comparison, a statistical linear regression model was built to predict the cutting force. Neural models were made using MATLAB, and linear regression models were made using Microsoft Excel. Finally, the results of three neural network models and a statistical linear regression model are presented.
Keywords:milling, artificial neural network, regression analysis, cutting forces


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