Kurum Yazarı "Germen, Emin" Scopus İndeksli Yayınlar Koleksiyonu İçin Listeleme
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Anomaly detection with self-organizing maps and effects of principal component analysis on feature vectors
Kızılören, Tevfik; Germen, Emin (2009)Network anomaly detection is the problem of scrutinizing of unauthorized use of computer systems over a network. In literature there are plenty different methods produced for detecting network anomalies and the process of ... -
Autopilot Project with Unmanned Robot
Seckin, Bilgin; Ayan, Tuna; Germen, Emin (Elsevier Science BV, 2012)Mobile robot is an important figure during the search and rescue application after the natural diseases such as earthquakes, fire, flooding. In the disaster areas, searching the sign of living bodies or investigating the ... -
Case studies on the use of neural networks in eutrophication modeling
Karul, C; Soyupak, S; Çilesiz, AF; AkbAy, Nuran; Germen, Emin (Elsevier Science BV, 2000)Artificial neural networks are becoming more and more common to be used in development of prediction models for complex systems as the theory behind them develops and the processing power of computers increase. A three ... -
Discrimination of faulty compressors and healthy one using Kohonen maps [Kohonen hari·ta kullanarak hatali ve saglikli kompresörleri·n ayriştirilmasi]
Germen, Emin; Kaya, A.; Ünlü, Ü. (2011)Kohonen's Self Organizing Map (SOM) is a very usable method for the classification problems. In this work SOM is used to classify the possible faults of Hermetic Compressors which are used in the refrigerators. In refrigerators ... -
Identification of acoustic spectra for fault detection in induction motors
Akçay, Hüseyin; Germen, Emin (IEEE, 2013)In this paper, we study fault detection problem for induction motors by using a recently developed cross-power spectral density estimation algorithm from sound measurements. In a test rig, from multiple experiments the ... -
Improving the resultant quality of Kohonen's self organizing map using stiffness factor
Germen, Emin (2005)The performance of Self Organizing Map (SOM) is always influenced by learn methods. The resultant quality of the topological formation of the SOM is also highly dependent onto the learning rate and the neighborhood function. ... -
Increasing the topological quality of Kohonen's self organising map by using a hit term
Germen, Emin (Institute of Electrical and Electronics Engineers Inc., 2002)The quality of the topology obtained at the end of the training period of Kohonen's self organizing map (SOM) is highly dependent on the learning rate and neighborhood function that are chosen at the beginning. The ... -
Induction Motor Identification from Acoustic Noise Spectrum by a Covariance Subspace Algorithm
Akçay, Hüseyin; Germen, Emin; Türkay, Semiha (IEEE Computer Society, 2018)In this paper, we study identification of induction motors by using a recently developed covariance-based subspace algorithm from sound measurements. The sound data are collected by an array of five-microphones placed ... -
Network traffic classification with self organizing maps
Kızılören, Tevfik; Germen, Emin (2007)Anomaly detection in network traffic is one of the most challenging topics in the study of computer science and networking. This paper introduces a classification method for analyzing network traffic behavior. In order to ... -
A new approach to estimate red parameters using global congestion notification
Yelbaşi, Ö.; Germen, Emin (2011)In communication networks, congestion avoidance in routers is one of the hottest topics. In this work, a new queue management approach is proposed on the RED (Random Early Detection) algorithm by monitoring the global ... -
A new approach to mathematical water quality modeling in reservoirs: Neural networks
Karul, C; Soyupak, S; Germen, Emin (Wiley-V C H Verlag GMBH, 1998)Neural Networks are becoming more and more valuable tools for system modeling and function approximation as computing power of microcomputers increase. Modeling of complex ecological systems such as reservoir limnology is ... -
Self Organizing Map (SOM) approach for classification of mechanical faults in induction motors
Germen, Emin; Ece, D. Gökhan; Gerek, Ömer Nezih (Springer-Verlag Berlin, 2007)In this work, Self Organizing Map (SOM) is used in order to detect and classify the broken rotor bars and misalignment type mechanical faults that often occur in induction motors which are widely used in industry. The ... -
Self Organizing Map (SOM) approach for classification of Power Quality events
Germen, Emin; Gökhan, Ece, D.; Gerek, Ömer Nezih (2005)In this work, Self Organizing Map (SOM) is used in order to classify the types of defections in electrical systems, known as Power Quality (PQ) events. The features for classifications are extracted from real time voltage ... -
A Self Organizing Map Based Approach for Congestion Avoidance in Autonomous Ip Networks
Yelbasi, Özen; Germen, Emin (Acad Sciences Czech Republic, Inst Computer Science, 2015)This work presents a Self Organizing Map (SOM) based queue management approach against congestion in autonomous Internet Protocol (IP) networks. The new queue management approach is proposed with consideration to the pros ... -
Sound based induction motor fault diagnosis using Kohonen self-organizing map
Germen, Emin; Başaran, Murat; Fidan, Mehmet (Academic Press LTD- Elsevier Science LTD, 2014)The induction motors, which have simple structures and design, are the essential elements of the industry. Their long-lasting utilization in critical processes possibly causes unavoidable mechanical and electrical defects ... -
Subspace-Based Identification of Acoustic Noise Spectra in Induction Motors
Akçay, Hüseyin; Germen, Emin (IEEE-Inst Electrical Electronics Engineers Inc, 2015)In this paper, we study the identification of acoustic noise spectra in induction motors by using a recently developed frequency-domain cross-power spectrum estimation algorithm. This algorithm is a noniterative high-resolution ...