Show/Hide Menu
Hide/Show Apps
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Open Science Policy
Open Science Policy
Open Access Guideline
Open Access Guideline
Postgraduate Thesis Guideline
Postgraduate Thesis Guideline
Communities & Collections
Communities & Collections
Help
Help
Frequently Asked Questions
Frequently Asked Questions
Guides
Guides
Thesis submission
Thesis submission
MS without thesis term project submission
MS without thesis term project submission
Publication submission with DOI
Publication submission with DOI
Publication submission
Publication submission
Supporting Information
Supporting Information
General Information
General Information
Copyright, Embargo and License
Copyright, Embargo and License
Contact us
Contact us
A Data Mining Approach for Modeling High-frequency Spectral Decay of Ground Motions for Northwestern Turkey
Date
2012-06-11
Author
Şişman, Fatma Nurten
Pekcan, Onur
Askan Gündoğan, Ayşegül
Metadata
Show full item record
Item Usage Stats
110
views
0
downloads
Cite This
URI
https://hdl.handle.net/11511/70854
Conference Name
EURO, The 22nd European Conference on Operational Research (2012)
Collections
Unverified, Conference / Seminar
Suggestions
OpenMETU
Core
A Methodology for Seismic Loss Estimation in Urban Regions Based on Ground-Motion Simulations
Ugurhan, Beliz; Askan Gündoğan, Ayşegül; Erberik, Murat Altuğ (2011-04-01)
Seismic vulnerability assessment of residential buildings in regions of high seismicity is an interdisciplinary problem requiring major inputs from fields of seismology and earthquake engineering. The basic two components of loss estimation methods are information on regional seismicity and building stock. This study presents a realistic loss estimation methodology where the first component, input ground motions, is obtained from regional ground-motion simulations using the stochastic finite-fault technique...
A deep learning approach for the transonic flow field predictions around airfoils
Duru, Cihat; Alemdar, Hande; Baran, Özgür Uğraş (2022-01-01)
Learning from data offers new opportunities for developing computational methods in research fields, such as fluid dynamics, which constantly accumulate a large amount of data. This study presents a deep learning approach for the transonic flow field predictions around airfoils. The physics of transonic flow is integrated into the neural network model by utilizing Reynolds-averaged Navier–Stokes (RANS) simulations. A detailed investigation on the performance of the model is made both qualitatively and quant...
A deep learning methodology for the flow field prediction around airfoils
Duru, Cihat; Baran, Özgür Uğraş; Alemdar, Hande; Department of Mechanical Engineering (2021-9-07)
This study aims to predict flow fields around airfoils using a deep learning methodology based on an encoder-decoder convolutional neural network. Neural network training and evaluation are performed from a set of computational fluid dynamics (CFD) solutions of the 2-D flow field around a group of known airfoils at a wide range of angles of attack. Reynolds averaged Navier-Stokes (RANS)-based CFD simulations are performed at a selected Mach number on the transonic regime on high-quality structured computati...
A genetic algorithm approach for verification of the syllable-based text compression technique
Üçoluk, Göktürk; Toroslu, İsmail Hakkı (SAGE Publications, 1997-01-01)
Provided that an easy mechanism exists for it, it is possible to decompose a text into strings that have lengths greater than one and occur frequently. Having in one hand the set of such frequently occurring strings and in the other the set of letters and symbols, it is possible to compress the text using Huffman coding over an alphabet which is a subset of the union of these two sets. Observations reveal that, in most cases, the maximal inclusion of the strings leads to an optimal length of compressed text...
A time-phased linear programming model for planning the lignite supply in Ankara area.
Evranos, Çetin; Department of Industrial Engineering (1973)
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
F. N. Şişman, O. Pekcan, and A. Askan Gündoğan, “A Data Mining Approach for Modeling High-frequency Spectral Decay of Ground Motions for Northwestern Turkey,” presented at the EURO, The 22nd European Conference on Operational Research (2012), Vilniaus, Litvanya, 2012, Accessed: 00, 2021. [Online]. Available: https://hdl.handle.net/11511/70854.