Guder, Mennan
Salor, Ozgul
Cadirci, Isik
In this paper, an integrated knowledge discovery strategy for high dimensional spatial power quality event data is proposed. Real time, distributed measuring of the electricity transmission system parameters provides huge number of time series power quality events. The proposed method aims to construct characteristic event distribution and interaction models for individual power quality sensors and the whole electricity transmission system by considering feasibility, time and accuracy concerns. In order to construct the knowledge and prediction model for the power quality domain; feature construction, feature selection, event clustering, and multi-class support vector machine supervised learning algorithms are employed.


Data Mining Framework for Power Quality Event Characterization of Iron and Steel Plants
Guder, Mennan; Salor, Ozgul; ÇADIRCI, IŞIK; Ozkan, Baris; Altintas, Erinc (2015-07-01)
In this paper, a power quality (PQ) knowledge discovery and modeling framework has been developed for both temporal and spatial PQ event data collected from transformer substations supplying iron and steel (I&S) plants. PQ event characteristics of various I&S plants have been obtained based on clustering and rule discovery techniques. The data are collected by the PQ analyzers, which detect the voltage sags, swells, and interruptions according to the IEC Standard 61000-4-30. The constructed clustering strat...
Interharmonics analysis of power signals with fundamental frequency deviation using Kalman filtering
Köse, Neslihan; Salor, Oezguel; Leblebicioğlu, Mehmet Kemal (2010-09-01)
In this paper a spectral decomposition-based method for interharmonic computation is proposed for power systems where the fundamental frequency fluctuates significantly. In the proposed method, the frequency domain components of the voltage waveform are obtained by Kalman filtering. Both the system fundamental frequency and the correct spectrum of the voltage waveform, and hence the exact interharrnonics are obtained. The proposed method is tested with both simulated and field data obtained from different e...
Mesh Learning for Object Classification using fMRI Measurements
Ekmekci, Ömer; Ozay, Mete; Oztekin, Ilke; GİLLAM, İLKE; Oztekin, Uygar (2013-09-18)
Machine learning algorithms have been widely used as reliable methods for modeling and classifying cognitive processes using functional Magnetic Resonance Imaging (fMRI) data. In this study, we aim to classify fMRI measurements recorded during an object recognition experiment. Previous studies focus on Multi Voxel Pattern Analysis (MVPA) which feeds a set of active voxels in a concatenated vector form to a machine learning algorithm to train and classify the cognitive processes. In most of the MVPA methods,...
Combining scaffolding for content and scaffolding for dialogue to support conceptual breakthroughs in understanding probability
Kazak, Sibel; Wegerif, Rupert; Fujita, Taro (2015-11-01)
In this paper, we explore the relationship between scaffolding, dialogue, and conceptual breakthroughs, using data from a design-based research study that focuses on the development of understanding of probability in 10-12 year old students. The aim of the study is to gain insight into how the combination of scaffolding for content using technology and scaffolding for dialogue can facilitate conceptual breakthroughs. We analyse video-recordings and transcripts of pairs and triads of students solving problem...
Nonlinear analysis of R/C low-rise shear walls
Mansour, Mohamad Y.; Dicleli, Murat; Lee, Jung Yoon (SAGE Publications, 2004-08-01)
An analysis method for predicting the response of low-rise shear walls under both monotonic and cyclic loading is presented in this paper. The proposed analysis method is based on the softened truss model theory but utilizes newly proposed cyclic constitutive relationships for concrete and steel bars obtained from cyclic shear testing. The successfulness of the analysis method, when combined with new materials constitutive relationships, is checked against the test results of 33 low-rise shear walls reporte...
Citation Formats
M. Guder, O. Salor, and I. Cadirci, “INTEGRATED INSTANCE-BASED AND KERNEL METHODS FOR POWER QUALITY KNOWLEDGE MODELING,” 2010, p. 352, Accessed: 00, 2020. [Online]. Available: