• Optimizing unit commitment technique for operating automated hydro-electric power plants 

  Arsenov, Arsen; Dimirovski, Georgi M. (Elsevier, 2004)

  A systems approach to optimized, energy efficient, hydro-electric power plant operation via commitment of optimum number of generating units has been elaborated and tested in a case study. The application case study is a ...

• Optimizing supervision and control for industrial furnaces: Predictive control based design 

  Dimirovski, Georgi M.; Dinibütün, A. Talha; Vukubratovic, Miomir K.; Zhao, J. (Elsevier, 2004)

  A systems re-engineering technique to integrated control and supervision for applications to industrial multi-zone furnaces has been elaborated by using known theories on generalized predictive control and nonlinear ...

• On uncontrollable non-linear dynamic systems: Analytic solutions for integral manifolds 

  Stefanovski, Jovan D.; Dimirovski, Georgi M. (IEEE, 2003)

  In this paper three solutions for invariant submanifolds of nonlinear control systems are presented. The first and the second are based on functional expansion, which can be obtained by differentiation of functions only. ...

• Model predictive control: real-time issues and RBF-ANN implementation 

  Lokvenec, Irena I.; Dimirovski, Georgi M. (Elsevier, 2003)

  Model predictive controls are control strategy in which the effect oF the control actions are evaluated many steps in the future to gain an optimal control action. According to this the number of calculations made is very ...

• Multimedia transfer over the internet: A control based improvement of AIMD algorithm 

  Jing, Yuanwei; Dimirovski, Georgi M. (IEEE, 2006)

  The known Additive Increase Multiplicative Decrease algorithm has been further investigated and a novel, improved TCP-friendly flow control algorithm derived. This algorithm provides basic flow congestion control for ...

• An improved demand forecasting model using deep learning approach and proposed decision integration strategy for supply chain 

  Kilimci, Zeynep Hilal; Akyüz, A. Okay; Uysal, Mitat; Akyokuş, Selim; Uysal, M. Ozan; Atak Bülbül, Berna; Ekmiş, Mehmet Ali (Wiley ; Hindawi, 2019)

  Demand forecasting is one of the main issues of supply chains. It aimed to optimize stocks, reduce costs, and increase sales, profit, and customer loyalty. For this purpose, historical data can be analyzed to improve demand ...

• Mood detection from physical and neurophysical data using deep learning models 

  Kilimci, Zeynep Hilal; Güven, Aykut; Uysal, Mitat; Akyokuş, Selim (Wiley ; Hindawi, 2019)

  Nowadays, smart devices as a part of daily life collect data about their users with the help of sensors placed on them. Sensor data are usually physical data but mobile applications collect more than physical data like ...

• Network traffic prediction using variational mode decomposition and multi-reservoirs echo state network 

  Han, Ying; Jing, Yuanwei; Li, Kun; Dimirovski, Georgi M. (IEEE, 2019)

  The network traffic prediction is significant for the network load pre-warning and network congestion control. But the nonlinearity and nonstationarity of the actual network traffic data would reduce the prediction accuracy. ...

• Complexity symbiosis of glia-neuron cells and computational cybernetics of hopfield recurrent network: Novel neuron model 

  Dimirovski, Georgi M.; Warwick, Kevin; Stefanovski , Jovan (IEEE, 2019)

  Science of artificial neural networks and relevant computing mechanisms since McCullock-Pitts artificial neuron (1943) up via neurons and networks of Anderson (1972), Barto et al (1983), Grosberg (1967, 1976), Hopfield ...

• A comparison of text classifiers on IT incidents using WEKA 

  İşcen, Erdal Sever; Gürbüz, Mustafa Zahid (IEEE, 2019)

  IT service management and incident management is a hot topic in every company which serves IT services and they require human effort to manage. In ITIL framework for IT service management, it's always useful to link the ...

• The evaluation of word embedding models and deep learning algorithms for Turkish text classification 

  Kilimci, Zeynep Hilal; Akyokuş, Selim (IEEE, 2019)

  The use of word embedding models and deep learning algorithms are currently the most common and popular trends to enhance the overall performance of a text classification/categorization system. Word embedding models are ...

• Metin özetleme için cümle seçim metotları 

  Güran, Aysun; Arslan, Sümeyra Nur; Kılıç, Esma; Diri, Banu (IEEE, 2014)

  Bu çalışmanın amacı, bir dokümandaki en önemli cümleleri seçerek ilgili dokümanın özetini çıkarmaktır. Bu amaçla 15 farklı cümle seçim metodu kullanılmıştır. Bu metotlar, 15 kadın ve 15 erkek olmak üzere, toplam 30 kişi ...

• Modelling study on post-stabilization dynamics of inflation in Macedonia 

  Petrevski, Goran; Andreeski, Cvetko J.; Dimirovski, Georgi M. (Elsevier, 2003)

  The experience from and recorded observations on economy stabilization programs implemented worldwide have clearly shown that there is sharp difference between the inflation dynamics during the implementation of such ...

• Motion control via telecommunication networks: Random time delays and a simple stability design 

  Okatan, Ali; Dimirovski, Georgi M. (Elsevier, 2003)

  Motion control and navigation via telecommunications networks as well as the control of other dynamical systems recently again came in the focus by a number of authors world-wide. It has been subject to extensive investigation ...

• Composite systems control by combined math-analytical and FS/NN computing approach 

  Dimirovski, Georgi M.; Jing, Yuanwei; Zhao, Jun; Zhang, Siying (IFAC, 2003)

  A control systems engineering approach, employing a two-level overall system architecture and different but compatible formalisms for system representation on the upper and lower levels, has been investigated in detail. ...

• Metin sınıflandırmada yumuşatma yöntemleriyle çok değişkenli Bernoulli modeli kullanarak örüntü tanıma 

  Kilimci, Zeynep Hilal; Akyokuş, Selim (IEEE, 2016)

  Bu yayında esasen metin sınıflandırma alanında n-gram modeller üzerine odaklandık. N-gram modellerin sınıflandırma başarısı üzerindeki etkisini ölçmek için Naïve Bayes sınıflandırıcıya çeşitli yumuşatma yöntemlerini ...

• Collective adaptation evolution of weighted complex networks: on syncronizability dependence 

  Jing, Yuanwei; Wang, Dan; Dimirovski, Georgi M. (IEEE, 2017)

  An innovated evolving network representation model to characterize weighted, complex, scale-free networks is proposed. A new node or a community is added to network in the process of evolution while emergences of new links ...

• The Analysis of text categorization represented with word embeddings using homogeneous classifiers 

  Kilimci, Zeynep Hilal; Akyokuş, Selim (IEEE, 2019)

  Text data mining is the process of extracting and analyzing valuable information from text. A text data mining process generally consists of lexical and syntax analysis of input text data, the removal of non-informative ...

• WAN networked control systems implemented by computer control: Sampled-data synthesis 

  Dimirovski, Georgi M.; Liu, Yunlong; Wang, Jiqiang (IEEE, 2017)

  A novel discrete-time synthesis for WAN-based computer control of networked control systems with a class of nonlinear plants is developed. Such a networked control systems are assumed to comprise an affine nonlinear plant ...

• Spektral yöntemler ve küme bölüntüleme yaklaşımlarıyla 3B nesne bilgilerinin sıkıştırılması 

  Konur, Umut; Bayazıt, Uluğ; Gürgen, Fikret; Orcay, Özgür (IEEE, 2006)

  We propose a mesh geometry coder that utilizes spectral methods and a set partitioning approach for coding the spectral coefficients. The spectral method of [1] not only achieved high rate-distortion performance on irregular ...

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