Ocena osnovnega nihajnega časa zidane stavbe z umetno nevronsko mrežo : diplomsko delo

Kumberger, Aljaž

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Title:	Ocena osnovnega nihajnega časa zidane stavbe z umetno nevronsko mrežo : diplomsko delo
Authors:	ID Kumberger, Aljaž (Author) ID Peruš, Iztok (Mentor) More about this mentor... ID Uranjek, Mojmir (Comentor)
Files:	VS_Kumberger_Aljaz_2022.pdf (2,41 MB) MD5: 8C992CE6C4DA45C82DAACE06B1CDC9B0
Language:	Slovenian
Work type:	Bachelor thesis/paper
Typology:	2.11 - Undergraduate Thesis
Organization:	FGPA - Faculty of Civil Engineering, Transportation Engineering and Architecture
Abstract:	V diplomskem delu so najprej opisani teoretični in praktični principi umetnih nevronskih mrež in osnove dinamike gradbenih konstrukcij. Zanimalo nas je, ali lahko s pomočjo umetnih nevronskih mrež določimo nihajni čas n-nadstropnega zidanega stanovanjskega objekta. Izračunali smo parametre masa, togost in strižni prerez. S pomočjo programa EAVEK smo izračunali prvi nihajni čas za določeno število primerov in te rezultate uporabili kot vhodne podatke za učenje UNM. Ta je nato ugotovila korelacije med vhodnimi in izhodnimi podatki. Izdelali smo grafe, ki ponazarjajo prvi nihajni čas glede na togost in maso. Grafe smo ločili po številu etaž od ena do pet. Ugotovili smo, da lahko s pomočjo grafov približno določimo prvi nihajni čas za poljubne zidane stavbe.
Keywords:	nihajni čas, umetna inteligenca, nevronske mreže, potresna analiza, dinamika.
Place of publishing:	Maribor
Place of performance:	Maribor
Publisher:	[A. Kumberger]
Year of publishing:	2022
Number of pages:	1 spletni vir (1 datoteka PDF (36 f., pril. loč. pag.))
PID:	20.500.12556/DKUM-82647
UDC:	624.04:004.8(043.2)
COBISS.SI-ID:	136197891
Publication date in DKUM:	08.09.2022
Views:	785
Downloads:	81
Metadata:
Categories:	KTFMB - FG
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Licences

License:	CC BY-NC-ND 4.0, Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International

Link:	http://creativecommons.org/licenses/by-nc-nd/4.0/
Description:	The most restrictive Creative Commons license. This only allows people to download and share the work for no commercial gain and for no other purposes.
Licensing start date:	29.08.2022

Secondary language

Language:	English
Title:	Estimation of the fundamental period of vibration of a masonry building using an artifical neural network
Abstract:	The thesis first describes the theoretical and practical principles of artificial neural networks and the basics of dynamics for structures. The goal was to find out if we could use artificial neural networks to determine the fundamental period of vibration for an n-floored masonry building. We calculated the parameters of mass, stiffness and shear surface. With the help of a program called EAVEK, we calculated the first period of vibration for a certain number of cases and used these results as input data for the learning of the neural network. It then found the correlations between the input and output data. We created graphs that represent the fundamental period of vibration in terms of stiffness and mass. The graphs were seperated by the quantity of floors ranging from one to five. We found out that with the help of graphs, we can approximate the fundamental period of vibration for almost any masonry building.
Keywords:	period of vibration, artificial intelligence, neural network, seismic analysis, dynamics.

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