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- Keyword
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- Classification (10)
- Machine learning (10)
- Support vector machine (8)
- Feature selection (7)
- Genetic algorithm (7)
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- Feature extraction (6)
- Optimization (6)
- Wireless sensor networks (6)
- Particle swarm optimization (5)
- Artificial neural network (4)
- Clustering (4)
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- Deep learning (4)
- Anomaly detection (3)
- Artificial bee colony (3)
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- Distributed generation (3)
- Electric vehicle (3)
- Fuzzy logic (3)
- Fuzzy logic control (3)
- Gravitational search algorithm (3)
- Image processing (3)
- K-means (3)
- Low power (3)
- Sentiment analysis (3)
- Social media (3)
- Social networks (3)
- Voltage stability (3)
- Artificial neural networks (2)
Articles 31 - 60 of 335
Full-Text Articles in Physical Sciences and Mathematics
Path-Oriented Random Testing Through Iterative Partitioning (Ip-Prt), Esmaeel Nikravan, Saeed Parsa
Path-Oriented Random Testing Through Iterative Partitioning (Ip-Prt), Esmaeel Nikravan, Saeed Parsa
Turkish Journal of Electrical Engineering and Computer Sciences
Path-oriented random testing aims at generating a uniformly distributed sequence of test data from a program input domain space to traverse a desired execution path of the program. To this aim, this article proposes a new algorithm to refine a program inputs domain space from invalid subdomains not covering the path. The validity of the subdomains is checked by a constraint propagation method against the path constraints (PCs). The proposed algorithm uses a divide and conquer technique to iteratively split the inputs domain into subdomains and each time refutes those subdomains that are inconsistent with the PCs. The remaining shrunken …
Electromagnetic Radiation Exposure Of Multioperator Co-Sited Urban Base Stations, Ni̇yazi̇ Korkut Uluaydin, Tomasz Dlugosz, Şaban Seli̇m Şeker
Electromagnetic Radiation Exposure Of Multioperator Co-Sited Urban Base Stations, Ni̇yazi̇ Korkut Uluaydin, Tomasz Dlugosz, Şaban Seli̇m Şeker
Turkish Journal of Electrical Engineering and Computer Sciences
Mobile network operators (MNOs) concurrently use different generations of wireless technologies. The base stations (BSs) of different technology generations are co-located in order to decrease operational costs. Furthermore, the MNOs cooperate in order to co-site their base stations. Such an urban site includes more than 25 actively radiating antennas on average with different frequencies and modulations. Electromagnetic radiation (EMR) measurements performed in such an environment may have reduced accuracy. In this paper, the authors propose a new approach for the measurement of EMR in multiple mobile technology interwoven urban BS sites, where more than one operator exists. The maintenance activities …
Sparsity-Based Three-Dimensional Image Reconstruction For Near-Field Mimo Radar Imaging, Fi̇gen S. Oktem
Sparsity-Based Three-Dimensional Image Reconstruction For Near-Field Mimo Radar Imaging, Fi̇gen S. Oktem
Turkish Journal of Electrical Engineering and Computer Sciences
Near-field multiple-input multiple-output (MIMO) radar imaging systems are of interest in diverse fields such as medicine, through-wall imaging, airport security, concealed weapon detection, and surveillance. The successful operation of these radar imaging systems highly depends on the quality of the images reconstructed from radar data. Since the underlying scenes can be typically represented sparsely in some transform domain, sparsity priors can effectively regularize the image formation problem and hence enable high-quality reconstructions. In this paper, we develop an efficient three-dimensional image reconstruction method that exploits sparsity in near-field MIMO radar imaging. Sparsity is enforced using total variation regularization, and the …
Community Detection In Complex Networks Using A New Agglomerative Approach, Majid Arasteh, Somayeh Alizadeh
Community Detection In Complex Networks Using A New Agglomerative Approach, Majid Arasteh, Somayeh Alizadeh
Turkish Journal of Electrical Engineering and Computer Sciences
Complex networks are used for the representation of complex systems such as social networks. Graph analysis comprises various tools such as community detection algorithms to uncover hidden data. Community detection aims to detect similar subgroups of networks that have tight interconnections with each other while, there is a sparse connection among different subgroups. In this paper, a greedy and agglomerative approach is proposed to detect communities. The proposed method is fast and often detects high-quality communities. The suggested method has several steps. In the first step, each node is assigned to a separated community. In the second step, a vertex …
Enhancing Face Pose Normalization With Deep Learning, Anil Çeli̇k, Nafi̇z Arica
Enhancing Face Pose Normalization With Deep Learning, Anil Çeli̇k, Nafi̇z Arica
Turkish Journal of Electrical Engineering and Computer Sciences
In this study, we propose a hybrid method for face pose normalization, which combines the 3-D model-based method with stacked denoising autoencoder (SDAE) deep network. Instead of applying a mirroring operation for the invisible face parts of the posed image, SDAE learns how to fill in those regions by a large set of training samples. In the performance evaluation, we compare the proposed method to four different pose normalization methods and investigate their effects on facial emotion recognition and verification problems in addition to visual quality tests. Methods evaluated in the experiments include 2-D alignment, 3-D model-based method, pure SDAE-based …
Adaptive Canonical Correlation Analysis For Harmonic Stimulation Frequencies Recognition In Ssvep-Based Bcis, Sahar Sadeghi, Ali Maleki
Adaptive Canonical Correlation Analysis For Harmonic Stimulation Frequencies Recognition In Ssvep-Based Bcis, Sahar Sadeghi, Ali Maleki
Turkish Journal of Electrical Engineering and Computer Sciences
Steady-state visual evoked potential (SSVEP) is the brain's response to quickly repetitive visual stimulus with a certain frequency. To increase the information transfer rate (ITR) in SSVEP-based systems, due to the frequency resolution restriction, we are forced to broaden the frequency range, which causes harmonic frequencies to come into the stimulation frequency range. Conventional canonical correlation analysis (CCA) may be associated with error for SSVEP frequency recognition at stimulation frequencies with harmonic relations. The number of harmonics considered to construct reference signals are determined adaptively; for frequencies whose second harmonic exists in the frequency range, two harmonics are used, and …
Bidding Strategy For Generators Considering Ramp Rates In A Day-Ahead Electricity Market, Satyendra Singh, Manoj Fozdar
Bidding Strategy For Generators Considering Ramp Rates In A Day-Ahead Electricity Market, Satyendra Singh, Manoj Fozdar
Turkish Journal of Electrical Engineering and Computer Sciences
In a day-ahead electricity market, competitive bidding strategy plays a vital role for power suppliers to maximize their profit. In this type of market, each power supplier submits a set of hourly production prices and offers capacity for the next period. The market operator, after receiving this data along with forecasted hourly load from the demand side, allocates production output to each unit. Power suppliers face the problem in trading their offers in the market, due to the uncertain behavior of competitive power suppliers and power demand. Therefore, the power supplier requires a suitable bidding strategy for handling uncertainty in …
A Robust Smes Control For Enhancing Stability Of Distribution Systems Fed From Intermittent Wind Power Generation, Sayed Said, Mokhtar Aly, Balint Hartmann
A Robust Smes Control For Enhancing Stability Of Distribution Systems Fed From Intermittent Wind Power Generation, Sayed Said, Mokhtar Aly, Balint Hartmann
Turkish Journal of Electrical Engineering and Computer Sciences
The voltage and frequency stability issues of power systems are the main challenges that arise from high penetration levels of wind energy systems. This paper presents an effective solution for voltage and frequency stability problems by using a superconducting magnetic energy storage (SMES) system controlled with a fuzzy logic controller (FLC). The proposed control system can suppress the voltage and frequency fluctuations due to the high variations of wind speed. In addition, the proposed control system is suitable for both balanced and unbalanced distribution systems with high penetration levels of wind turbines (WTs). A squirrel cage induction generator (SCIG) is …
A Distributed Load Balancing Algorithm For Deduplicated Storage, Prabavathy Balasundaram, Chitra Babu, Pradeep Rengaswamy
A Distributed Load Balancing Algorithm For Deduplicated Storage, Prabavathy Balasundaram, Chitra Babu, Pradeep Rengaswamy
Turkish Journal of Electrical Engineering and Computer Sciences
While deduplication brings the advantage of significant space savings in storage, it nevertheless incurs the overhead of maintaining huge metadata. Updating such huge metadata during the data migration that arises due to load balancing activity results in significant overhead. In order to reduce this metadata update overhead, this paper proposes a suitable alternate index that tracks the data blocks even when they migrate across the nodes without explicitly storing the location information. In addition, a virtual server-based load balancing (VSLB) algorithm has been proposed in order to reduce the migration overhead. The experimental results indicate that the proposed index reduces …
On The Performance Of Quick Artificial Bee Colony Algorithm For Dynamic Deployment Of Wireless Sensor Networks, Beyza Gorkemli, Zahraa Al-Dulaimi
On The Performance Of Quick Artificial Bee Colony Algorithm For Dynamic Deployment Of Wireless Sensor Networks, Beyza Gorkemli, Zahraa Al-Dulaimi
Turkish Journal of Electrical Engineering and Computer Sciences
In recent years, the use of wireless sensor networks (WSNs) has increased and there have been significant improvements in this field. Especially with smarter, cheaper, and smaller sensor nodes, various kinds of information can be detected and collected in different environments and under different conditions. WSNs have thus been used in many applications such as military, surveillance, target tracking, home, medical, and environmental applications. As the popularity of WSNs increases, problems related to these networks are being realized. The dynamic deployment problem is one of the main challenges that have a direct effect on the performance of WSNs. In this …
A Novel Randomized Recurrent Artificial Neural Network Approach: Recurrent Random Vector Functional Link Network, Ömer Faruk Ertuğrul
A Novel Randomized Recurrent Artificial Neural Network Approach: Recurrent Random Vector Functional Link Network, Ömer Faruk Ertuğrul
Turkish Journal of Electrical Engineering and Computer Sciences
The random vector functional link (RVFL) has successfully been employed in many applications since 1989. RVFL has a single hidden layer feedforward structure that also has direct links between the input layer and the output layer. Although nonlinearity, high generalization capacity, and fast training ability can be provided in RVFL, it can be found from the literature that higher nonlinearity can be obtained by adding recurrent feedback to an artificial neural network. In this paper, the recurrent type of RVFL (R-RVFL), which has both outer feedbacks and also inner feedbacks, is proposed. In order to evaluate and validate the proposed …
Empirical Model Development For The Estimation Of Clearness Index Using Meteorological Parameters, Fakhar Alam, Saif Ur Rehman, Shafiqur Rehman, Muhammad Jahangir, Muhammad Shoaib, Imran Siddiqui, Intikhab Ulfat
Empirical Model Development For The Estimation Of Clearness Index Using Meteorological Parameters, Fakhar Alam, Saif Ur Rehman, Shafiqur Rehman, Muhammad Jahangir, Muhammad Shoaib, Imran Siddiqui, Intikhab Ulfat
Turkish Journal of Electrical Engineering and Computer Sciences
The clearness index is an indispensable parameter required for the design and analysis of solar energy systems. In the absence of measured values for a specific location, the clearness index can be estimated from other measured meteorological variables. In this study three meteorological parameters, sunshine hours, monthly mean values of the temperature difference ($\Delta$T), and cloudiness, are used to develop empirical models for the estimation of clearness index. The empirical models are developed for five major cities in Pakistan (Karachi, Multan, Lahore, Islamabad, and Quetta). For empirical model development, long-term data (1991 to 2010) of monthly average clearness index, sunshine …
Line Independency-Based Network Modelling For Backward/Forward Load Flow Analysis Of Electrical Power Distribution Systems, Reyhaneh Taheri, Alimorad Khajezadeh, Mohammad Hossein Rezaeian Koochi, Abbas Sharifi Nasab Anari
Line Independency-Based Network Modelling For Backward/Forward Load Flow Analysis Of Electrical Power Distribution Systems, Reyhaneh Taheri, Alimorad Khajezadeh, Mohammad Hossein Rezaeian Koochi, Abbas Sharifi Nasab Anari
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper a straightforward method for line independency-based modelling of electrical power distribution systems is proposed. The proposed method can determine the backward and forward sweeping routes of distribution systems for calculating line currents and bus voltages. To do that, the method identifies the independent lines in consecutive steps. An independent line is a line in the distribution system whose current does not depend on the current of other lines in the system. The proposed line independency-based network modelling is required to be performed only once and prior to the load flow analysis. The output of the proposed method, …
Optimal Siting, Sizing, And Parameter Tuning Of Statcom And Sssc Using Mpso And Remote Coordination Of The Facts For Oscillation Damping Of Power Systems, James Garba Ambafi, Sunusi Sani Adamu
Optimal Siting, Sizing, And Parameter Tuning Of Statcom And Sssc Using Mpso And Remote Coordination Of The Facts For Oscillation Damping Of Power Systems, James Garba Ambafi, Sunusi Sani Adamu
Turkish Journal of Electrical Engineering and Computer Sciences
In electromechanical oscillation damping within power system, power system stabilizers (PSSs) are often deployed. However, a PSS is less effective in damping interarea oscillation and is limited by changes in network configuration due to weak tie-lines and load variations. Consequently, this paper presents a wide-area coordination approach that damps interarea oscillations using FACTS devices and phasor measurement units. We selected a static synchronous compensator (STATCOM) and static series synchronous compensator (SSSC) for realistic power system interarea oscillation damping. The performance of the coordinated FACTS installed in a power system depends on their suitable locations, sizes, tuned parameters, and remote input …
Predicting Co And Nox Emissions From Gas Turbines: Novel Data And A Benchmark Pems, Heysem Kaya, Pinar Tüfekci̇, Erdi̇nç Uzun
Predicting Co And Nox Emissions From Gas Turbines: Novel Data And A Benchmark Pems, Heysem Kaya, Pinar Tüfekci̇, Erdi̇nç Uzun
Turkish Journal of Electrical Engineering and Computer Sciences
Predictive emission monitoring systems (PEMS) are important tools for validation and backing up of costly continuous emission monitoring systems used in gas-turbine-based power plants. Their implementation relies on the availability of appropriate and ecologically valid data. In this paper, we introduce a novel PEMS dataset collected over five years from a gas turbine for the predictive modeling of the CO and NOx emissions. We analyze the data using a recent machine learning paradigm, and present useful insights about emission predictions. Furthermore, we present a benchmark experimental procedure for comparability of future works on the data
Adaptive Iir Filter Design Using Self-Adaptive Search Equation Based Artificial Bee Colony Algorithm, Burhanetti̇n Durmuş, Gürcan Yavuz, Doğan Aydin
Adaptive Iir Filter Design Using Self-Adaptive Search Equation Based Artificial Bee Colony Algorithm, Burhanetti̇n Durmuş, Gürcan Yavuz, Doğan Aydin
Turkish Journal of Electrical Engineering and Computer Sciences
Infinite impulse response (IIR) system identification problem is defined as an IIR filter modeling to represent an unknown system. During a modeling task, unknown system parameters are estimated by metaheuristic algorithms through the IIR filter. This work deals with the self-adaptive search-equation-based artificial bee colony (SSEABC) algorithm that is adapted to optimal IIR filter design. SSEABC algorithm is a recent and improved variant of artificial bee colony (ABC) algorithm in which appropriate search equation is determined with a self-adaptive strategy. Moreover, the success of the SSEABC algorithm enhanced with a competitive local search selection strategy was proved on benchmark functions …
Damping Of Low-Frequency Oscillation In Power Systems Using Hybrid Renewable Energy Power Plants, Mahdi Saadatmand, Babak Mozafari, Gevork Babamalek Gharehpetian, Soodabeh Soleymani
Damping Of Low-Frequency Oscillation In Power Systems Using Hybrid Renewable Energy Power Plants, Mahdi Saadatmand, Babak Mozafari, Gevork Babamalek Gharehpetian, Soodabeh Soleymani
Turkish Journal of Electrical Engineering and Computer Sciences
Global warming, increase in environmental pollution, and high cost of electrical power generation using fossil fuels are considered the most important reasons for the application of renewable energy power plants (REPPs) around the world. In recent years, a new generation of REPPs called hybrid renewable energy power plants (HREPPs) has been implemented in order to have higher efficiency and reliability than conventional REPPs such as wind power plants and photovoltaic power plants. The HREPPs include two or more renewable energy generation units such as wind turbine generation units, and PV generation units. In case of high penetration of these types …
Electron Energy Loss Spectroscopy Simulation By A Frequency Domain Surface Integral Equation Solver, İsmai̇l Enes Uysal
Electron Energy Loss Spectroscopy Simulation By A Frequency Domain Surface Integral Equation Solver, İsmai̇l Enes Uysal
Turkish Journal of Electrical Engineering and Computer Sciences
Plasmonic nanoparticles have been mostly studied using conventional light sources. Recently, electron energy loss spectroscopy (EELS) has started to be used to analyze plasmonic nanoparticles where incident electromagnetic fields are created by swift electrons. To accurately simulate EELS experiments, several numerical methods have been adapted. In this paper, a frequency domain surface integral equation (FDSIE) solver is modified to simulate EELS for plasmonic nanoparticles of gold and silver. Accuracy and versatility of the proposed FDSIE solver are shown by several numerical examples and compared to existing numerical, analytical, and experimental results.
A Memory-Efficient Canonical Data Structure For Decimal Floating Point Arithmetic Systems Modeling And Verification, Mohammad Saeed Jahangiry, Saeed Safari
A Memory-Efficient Canonical Data Structure For Decimal Floating Point Arithmetic Systems Modeling And Verification, Mohammad Saeed Jahangiry, Saeed Safari
Turkish Journal of Electrical Engineering and Computer Sciences
Decimal floating point (DFP) number representation was proposed in IEEE-754-2008 in order to overcome binary floating point inaccuracy. Neglecting binary floating point verification has resulted in significant validity and economic losses. Formal verification can be a solution to similar DFP design problems. Verification techniques aiming at DFP are limited to functional methods whereas formal approaches have been neglected and traditional decision diagrams cannot model DFP representation complexity. In this paper, we propose an efficient canonical data structure that can model DFP properties. Our novel data structure models coefficient, exponent, sign, and bias of a DFP number. We will prove mathematically …
A Kalman Filter Application For Rainfall Estimation Using Radar Reflectivity Measurements, Engi̇n Maşazade, Ali̇ Kemal Bakir, Pinar Kirci
A Kalman Filter Application For Rainfall Estimation Using Radar Reflectivity Measurements, Engi̇n Maşazade, Ali̇ Kemal Bakir, Pinar Kirci
Turkish Journal of Electrical Engineering and Computer Sciences
The rainfall amount observed at a given location mostly depend on the cloud density, which can be quantified with the reflectivity values observed by meteorology weather radars. In this study, we aim to estimate the rainfall amount using a Kalman filter with radar reflectivity measurements. We first assume that the amount of rainfall observed at automatic weather observation stations (AWOSs) are elements of an unknown state vector and consider the Kalman filter process model as the true rainfall amounts observed at these AWOSs over time. For the measurement model of the Kalman filter, we use the radar reflectivity values observed …
An Improved Tree Model Based On Ensemble Feature Selection For Classification, Chandralekha M, Shenbagavadivu N
An Improved Tree Model Based On Ensemble Feature Selection For Classification, Chandralekha M, Shenbagavadivu N
Turkish Journal of Electrical Engineering and Computer Sciences
Researchers train and build specific models to classify the presence and absence of a disease and the accuracy of such classification models is continuously improved. The process of building a model and training depends on the medical data utilized. Various machine learning techniques and tools are used to handle different data with respect to disease types and their clinical conditions. Classification is the most widely used technique to classify disease and the accuracy of the classifier largely depends on the attributes. The choice of the attribute largely affects the diagnosis and performance of the classifier. Due to growing large volumes …
A Hybrid Model For The Prediction Of Aluminum Foil Output Thickness In Cold Rolling Process, Ali̇ Öztürk, Ri̇fat Şeherli̇
A Hybrid Model For The Prediction Of Aluminum Foil Output Thickness In Cold Rolling Process, Ali̇ Öztürk, Ri̇fat Şeherli̇
Turkish Journal of Electrical Engineering and Computer Sciences
This study proposes a hybrid model composed of multiple prediction algorithms and an autoregressive moving average (ARMA) module for the thickness prediction. In order to attain higher accuracy, the prediction algorithms were globally combined by simple voting to reduce the effect of the inductive bias imposed by each algorithm on the dataset. The global multiexpert combination (GMEC) system included the multilayer perceptron neural network (MLPNN), radial basis function network (RBFN), multiple linear regression (MLR), and support vector machines (SVM) algorithms. The proposed hybrid model extends the GMEC system by integrating an ARMA module for the output. On the test dataset, …
Extending A Sentiment Lexicon With Synonym--Antonym Datasets: Swnettr++, Fati̇h Sağlam, Burkay Genç, Hayri̇ Sever
Extending A Sentiment Lexicon With Synonym--Antonym Datasets: Swnettr++, Fati̇h Sağlam, Burkay Genç, Hayri̇ Sever
Turkish Journal of Electrical Engineering and Computer Sciences
In our previous studies on developing a general-purpose Turkish sentiment lexicon, we constructed SWNetTR-PLUS, a sentiment lexicon of 37K words. In this paper, we show how to use Turkish synonym and antonym word pairs to extend SWNetTR-PLUS by almost 33 % to obtain SWNetTR++, a Turkish sentiment lexicon of 49K words. The extension was done by transferring the problem into the graph domain, where nodes are words, and edges are synonym--antonym relations between words, and propagating the existing tone and polarity scores to the newly added words using an algorithm we have developed. We tested the existing and new lexicons …
Queue Length Feedback-Based Solution Of Tcp Incast In Data Center Networks, Hasnain Ahmed, Junaid Arshad
Queue Length Feedback-Based Solution Of Tcp Incast In Data Center Networks, Hasnain Ahmed, Junaid Arshad
Turkish Journal of Electrical Engineering and Computer Sciences
The Internet offers a large number of applications and services that we use on a daily basis. These widely used applications are hosted on large-scale, high-performance computing systems called data centers. The performance of TCP is inefficient in many-to-one communication, which is a common traffic pattern in data center networks. This many-to-one communication causes significant packet losses followed by timeouts, which consequently results in throughput collapse in data center networks; this problem is known as TCP Incast. In this paper, we present a queue length feedback-based solution to mitigate TCP Incast. The scheme has two parts: i) a novel queue …
Particle Swarm Optimization-Based Collision Avoidance, Ti̇mur İnan, Ahmet Fevzi̇ Baba
Particle Swarm Optimization-Based Collision Avoidance, Ti̇mur İnan, Ahmet Fevzi̇ Baba
Turkish Journal of Electrical Engineering and Computer Sciences
Collision risk assessment and collision avoidance of vessels have always been an important topic in ocean engineering. Decision support systems are increasingly becoming the focus of many studies in the maritime industry today as vessel accidents are often caused by human error. This study proposes an anticollision decision support system that can determine surrounding obstacles by using the information received from radar systems, obtain the position and speed of obstacles within a certain time period, and suggest possible routes to prevent collisions. In this study we use a neural network to predict the subsequent positions of surrounding vessels, a fuzzy …
Verifiable Dynamic Searchable Encryption, Mohammad Etemad, Alpteki̇n Küpcü
Verifiable Dynamic Searchable Encryption, Mohammad Etemad, Alpteki̇n Küpcü
Turkish Journal of Electrical Engineering and Computer Sciences
Using regular encryption schemes to protect the privacy of the outsourced data implies that the client should sacrifice functionality for security. Searchable symmetric encryption (SSE) schemes encrypt the data in a way that the client can later search and selectively retrieve the required data. Many SSE schemes have been proposed, starting with static constructions, and then dynamic and adaptively secure constructions but usually in the honest-but-curious model. We propose a verifiable dynamic SSE scheme that is adaptively secure against malicious adversaries. Our scheme supports file modification, which is essential for efficiently working with large files, in addition to the ability …
A Hybrid Single-Source Shortest Path Algorithm, Hi̇lal Arslan, Murat Manguoğlu
A Hybrid Single-Source Shortest Path Algorithm, Hi̇lal Arslan, Murat Manguoğlu
Turkish Journal of Electrical Engineering and Computer Sciences
The single-source shortest path problem arises in many applications, such as roads, social applications, and computer networks. Finding the shortest path is challenging, especially for graphs that contain a large number of vertices and edges. In this work, we propose a novel hybrid method that first sparsifies a given graph by removing most edges that cannot form the shortest path tree and then applies a classical shortest path algorithm to the sparser graph. Removing all the edges that cannot form the shortest path tree would be expensive since it is equivalent to solving the original problem. Therefore, we propose an …
Modified Self-Adaptive Local Search Algorithm For A Biobjective Permutation Flowshop Scheduling Problem, Çi̇ğdem Alabaş Uslu, Berna Dengi̇z, Canan Ağlan, İhsan Sabuncuoğlu
Modified Self-Adaptive Local Search Algorithm For A Biobjective Permutation Flowshop Scheduling Problem, Çi̇ğdem Alabaş Uslu, Berna Dengi̇z, Canan Ağlan, İhsan Sabuncuoğlu
Turkish Journal of Electrical Engineering and Computer Sciences
Interest in multiobjective permutation flow shop scheduling (PFSS) has increased in the last decade to ensure effective resource utilization. This study presents a modified self-adaptive local search (MSALS) algorithm for the biobjective permutation flow shop scheduling problem where both makespan and total flow time objectives are minimized. Compared to existing sophisticated heuristic algorithms, MSALS is quite simple to apply to different biobjective PFSS instances without requiring effort or time for parameter tuning. Computational experiments showed that MSALS is either superior to current heuristics for Pareto sets or is incomparable due to other performance indicators of multiobjective problems.
Optimal Dg Allocation For Enhancing Voltage Stability And Minimizing Power Loss Using Hybrid Gray Wolf Optimizer, Salah Kamel, Ayman Awad, Hussein Abdel-Mawgoud, Francisco Jurado
Optimal Dg Allocation For Enhancing Voltage Stability And Minimizing Power Loss Using Hybrid Gray Wolf Optimizer, Salah Kamel, Ayman Awad, Hussein Abdel-Mawgoud, Francisco Jurado
Turkish Journal of Electrical Engineering and Computer Sciences
High penetration of photovoltaic and wind turbine-based distributed generators (DGs) can help reduce carbon emissions which is an important goal for the whole world. DG can be used to improve the voltage stability, present generation reserve/emergency, and consequently, the system power quality can be improved. However, it is very important to select the right size and location of a DG so that the power system can increase the gained benefits of such an installation to the maximum. In this paper, a hybrid optimization technique is proposed to determine the optimal allocation of DG in the standard IEEE 33-bus radial distribution …
Unsupervised Deep Feature Embeddings For Speaker Diarization, Rehan Ahmad, Syed Zubair
Unsupervised Deep Feature Embeddings For Speaker Diarization, Rehan Ahmad, Syed Zubair
Turkish Journal of Electrical Engineering and Computer Sciences
Speaker diarization aims to determine ?who spoke when?? from multispeaker recording environments. In this paper, we propose to learn a set of high-level feature representations, referred to as feature embeddings, from an unsupervised deep architecture for speaker diarization. These sets of embeddings are learned through a deep autoencoder model when trained on mel-frequency cepstral coefficients (MFCCs) of input speech frames. Learned embeddings are then used in Gaussian mixture model based hierarchical clustering for diarization. The results show that these unsupervised embeddings are better compared to MFCCs in reducing the diarization error rate. Experiments conducted on the popular subset of the …