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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)
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- Artificial bee colony (3)
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- Image processing (3)
- K-means (3)
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- Social networks (3)
- Voltage stability (3)
- Artificial neural networks (2)
Articles 1 - 30 of 335
Full-Text Articles in Physical Sciences and Mathematics
Convex Polygon Triangulation Based On Planted Trivalent Binary Tree\\ And Ballot Problem, Muzafer Saracevic, Aybeyan Seli̇mi̇
Convex Polygon Triangulation Based On Planted Trivalent Binary Tree\\ And Ballot Problem, Muzafer Saracevic, Aybeyan Seli̇mi̇
Turkish Journal of Electrical Engineering and Computer Sciences
This paper presents a new technique of generation of convex polygon triangulation based on planted trivalent binary tree and ballot notation. The properties of the Catalan numbers were examined and their decomposition and application in developing the hierarchy and triangulation trees were analyzed. The method of storage and processing of triangulation was constructed on the basis of movements through the polygon. This method was derived from vertices and leaves of the planted trivalent binary tree. The research subject of the paper is analysis and comparison of a constructed method for solving of convex polygon triangulation problem with other methods and …
A Novel Accuracy Assessment Model For Video Stabilization Approaches Based On Background Motion, Md Alamgir Hossain, Tien-Dung Nguyen, Eui Nam Huh
A Novel Accuracy Assessment Model For Video Stabilization Approaches Based On Background Motion, Md Alamgir Hossain, Tien-Dung Nguyen, Eui Nam Huh
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper, we propose a new accuracy measurement model for the video stabilization method based on background motion that can accurately measure the performance of the video stabilization algorithm. Undesired residual motion present in the video can quantitatively be measured by the pixel by pixel background motion displacement between two consecutive background frames. First of all, foregrounds are removed from a stabilized video, and then we find the two-dimensional flow vectors for each pixel separately between two consecutive background frames. After that, we calculate a Euclidean distance between these two flow vectors for each pixel one by one, which …
Hybix: A Novel Encoding Bitmap Index For Space- And Time-Efficient Query Processing, Naphat Keawpibal, Ladda Preechaveerakul, Sirirut Vanichayobon
Hybix: A Novel Encoding Bitmap Index For Space- And Time-Efficient Query Processing, Naphat Keawpibal, Ladda Preechaveerakul, Sirirut Vanichayobon
Turkish Journal of Electrical Engineering and Computer Sciences
A bitmap-based index is an effective and efficient indexing method for answering selective queries in a read-only environment. It offers improved query execution time by applying low-cost Boolean operators on the index directly, before accessing raw data. A drawback of the bitmap index is that index size increases with the cardinality of indexed attributes, which additionally has an impact on a query execution time. This impact is related to an increase of query execution time due to the scanning of bitmap vectors to answer the queries. In this paper, we propose a new encoding bitmap index, called the HyBiX bitmap …
A Novel Hybrid Teaching-Learning-Based Optimization Algorithm For The Classification Of Data By Using Extreme Learning Machines, Ender Sevi̇nç, Tansel Dökeroğlu
A Novel Hybrid Teaching-Learning-Based Optimization Algorithm For The Classification Of Data By Using Extreme Learning Machines, Ender Sevi̇nç, Tansel Dökeroğlu
Turkish Journal of Electrical Engineering and Computer Sciences
Data classification is the process of organizing data by relevant categories. In this way, the data can be understood and used more efficiently by scientists. Numerous studies have been proposed in the literature for the problem of data classification. However, with recently introduced metaheuristics, it has continued to be riveting to revisit this classical problem and investigate the efficiency of new techniques. Teaching-learning-based optimization (TLBO) is a recent metaheuristic that has been reported to be very effective for combinatorial optimization problems. In this study, we propose a novel hybrid TLBO algorithm with extreme learning machines (ELM) for the solution of …
Invisible Watermarking Framework That Authenticates And Prevents The Visualization Of Anaglyph Images For Copyright Protection, David-Octavio Muñoz-Ramirez, Volodymyr Ponomaryov, Rogelio Reyes-Reyes, Clara Cruz-Ramos, Beatriz-Paulina Garcia-Salgado
Invisible Watermarking Framework That Authenticates And Prevents The Visualization Of Anaglyph Images For Copyright Protection, David-Octavio Muñoz-Ramirez, Volodymyr Ponomaryov, Rogelio Reyes-Reyes, Clara Cruz-Ramos, Beatriz-Paulina Garcia-Salgado
Turkish Journal of Electrical Engineering and Computer Sciences
In this work, a watermarking framework to authenticate and protect the copyright that prevents the visualization of nonauthorized anaglyph images is proposed. Designed scheme embeds a binary watermark and the Blue channel of the anaglyph image into the discrete cosine transform domain of the original image. The proposed method applies the quantization index modulation-dither modulation algorithm and a combination of Bose-Chaudhuri-Hocquenghem with repetition codes, which permit to increase the capability in recovering the watermark. Additionally, Hash algorithm is used to scramble the component where the watermark should be embedding, guaranteeing a higher security performance of the scheme. This new technique …
Combined Feature Compression Encoding In Image Retrieval, Lu Huo, Leijie Zhang
Combined Feature Compression Encoding In Image Retrieval, Lu Huo, Leijie Zhang
Turkish Journal of Electrical Engineering and Computer Sciences
Recently, features extracted by convolutional neural networks (CNNs) are popularly used for image retrieval. In CNN representation, high-level features are usually chosen to represent the images in coarse-grained datasets, while mid-level features are successfully applied to describe the images for fine-grained datasets. In this paper, we combine these different levels of features as a joint feature to propose a robust representation that is suitable for both coarse-grained and fine-grained image retrieval datasets. In addition, in order to solve the problem that the efficiency of image retrieval is influenced by the dimensionality of indexing, a unified subspace learning model named spectral …
Design Of A Portable And Low-Cost Mass-Sensitive Sensor With The Capability Of Measurements On Various Frequency Quartz Tuning Forks, Mehmet Altay Ünal, İsmai̇l Cengi̇z Koçum, Di̇lek Çökeli̇ler Serdaroğlu
Design Of A Portable And Low-Cost Mass-Sensitive Sensor With The Capability Of Measurements On Various Frequency Quartz Tuning Forks, Mehmet Altay Ünal, İsmai̇l Cengi̇z Koçum, Di̇lek Çökeli̇ler Serdaroğlu
Turkish Journal of Electrical Engineering and Computer Sciences
Recently, sensor and biosensor applications have become widespread and are now significant tools in the biomedical field and other areas. Since quartz tuning fork (QTF) resonance frequency depends on the mass adsorbed to its prongs, it is generally used to measure minor mass change and detect target analyte in picogram levels. This study is undertaken to design and fabricate a sensor device for the measurement of QTF transducers. When QTF sensor studies were investigated, it was found that explanations on the details of instrumentation part were limited, and in addition, there was no compact commercial products. In this study, a …
A Comparative Study Of Nonlinear Bayesian Filtering Algorithms For Estimation Ofgene Expression Time Series Data, Nesrine Amor, Asma Meddeb, Sahbi Marrouchi, Souad Chebbi
A Comparative Study Of Nonlinear Bayesian Filtering Algorithms For Estimation Ofgene Expression Time Series Data, Nesrine Amor, Asma Meddeb, Sahbi Marrouchi, Souad Chebbi
Turkish Journal of Electrical Engineering and Computer Sciences
This paper addresses the problem of estimating the time series of a gene expression using nonlinear Bayesian filtering algorithms. The response of gene regulatory networks (GRNs) to functional requirements in the cell and environmental conditions evolves over time. Dynamic biological processes such as cancer progression and treatment recovery depend on the collected genetic profiles. These processes are behind genetic interactions that rewire over the course of time. The GRN was formulated as a nonlinear and non-Gaussian dynamic system defined by the gene measurement model and the unknown state is an evolution of the gene model. However, the GRN has a …
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 …
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 …
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 …
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 …
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 …
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 …
A Depth-Based Nearest Neighbor Algorithmfor High-Dimensional Data Classification, Sandhya Harikumar, Akhil A.S, Ramachandra Kaimal
A Depth-Based Nearest Neighbor Algorithmfor High-Dimensional Data Classification, Sandhya Harikumar, Akhil A.S, Ramachandra Kaimal
Turkish Journal of Electrical Engineering and Computer Sciences
Nearest neighbor algorithms like k-nearest neighbors (kNN) are fundamental supervised learning techniques to classify a query instance based on class labels of its neighbors. However, quite often, huge volumes of datasets are not fully labeled and the unknown probability distribution of the instances may be uneven. Moreover, kNN suffers from challenges like curse of dimensionality, setting the optimal number of neighbors, and scalability for high-dimensional data. To overcome these challenges, we propose an improvised approach of classification via depth representation of subspace clusters formed from high-dimensional data. We offer a consistent and principled approach to dynamically choose the nearest neighbors …
Optimal Placement Of Switching And Protection Devices In Radial Distribution Networks To Enhance System Reliability Using The Ahp-Pso Method, Masoud Amohadi, Mahmud Fotuhi Firuzabad
Optimal Placement Of Switching And Protection Devices In Radial Distribution Networks To Enhance System Reliability Using The Ahp-Pso Method, Masoud Amohadi, Mahmud Fotuhi Firuzabad
Turkish Journal of Electrical Engineering and Computer Sciences
This paper presents a new method to determine the optimal number and locations of autorecloser and sectionalizer switches (AR/S) in distribution networks. The costs of AR/S investment, switch maintenance, and undistributed energy as well as reliability coefficients are considered in the objective function. Reliability parameters such as SAIFI, SADI, MAIFI, and ENS are evaluated in the case study system. As a new method, the weights of the reliability parameters are obtained by decision-makers using the analytical hierarchy process (AHP). The optimal size, type, and location of automatic switches are determined by minimizing the objective function using the particle swarm optimization …
A Novel Design Of An Electromagnetically Levitated Vibrational Viscometer For Biomedical And Clinical Applications, Ali̇ Akpek
Turkish Journal of Electrical Engineering and Computer Sciences
Accurate determination of the viscosity behavior of fluids is extremely important, especially for biomedical and clinical applications. For example, blood viscosity is used to detect cardiovascular diseases in patients. Like blood, all body fluids and biochemical solvents used in biomedical studies are very limited resources. Therefore, a viscometer that is especially focused for biomedical and clinical applications should have the ability to obtain viscosity results from a reservoir as small as possible, in a range as wide as possible and in a period of time as short as possible. The measurements must be accurate even when the fluid temperatures shift …
Evaluation Of Losses In A Secondary-Side Controlled Wireless Battery Charging System, Fahri̇ Gürbüz, Tolga Sürgevi̇l, Mutlu Boztepe
Evaluation Of Losses In A Secondary-Side Controlled Wireless Battery Charging System, Fahri̇ Gürbüz, Tolga Sürgevi̇l, Mutlu Boztepe
Turkish Journal of Electrical Engineering and Computer Sciences
Secondary-side controlled inductive power transfer (IPT) systems are easy to control compared to primary and dual-side control methods, and more importantly, they do not require wireless communication between primary and secondary sides. In this paper, a wireless battery charging system based on secondary-side controlled IPT is analyzed and presented in detail. The proposed control method relies on the detection of the secondary coil current and the transferred power can be fully controlled by the secondary-side active rectifier with reduced number of power switching devices. The steady-state performance of the IPT system is evaluated using a fundamental harmonic analysis method for …
Prioritizing Interdependent Software Requirements Using Tensor And Fuzzy Graphs, Negin Misaghian, Homayun Motameni, Mohsen Rabbani
Prioritizing Interdependent Software Requirements Using Tensor And Fuzzy Graphs, Negin Misaghian, Homayun Motameni, Mohsen Rabbani
Turkish Journal of Electrical Engineering and Computer Sciences
Owing to the special stance of prioritizing tasks in requirements engineering processes, and as the requirements are not independent in nature, considering their dependencies is essential during the prioritizing process. Although different classifications of dependency types among requirements exist, only a few approaches in the prioritization process consider such valuable data (dependency among equirements). To achieve a practical prioritization, this study proposes a method based on the effects of the requirement dependencies (increase/decrease cost of) on the value of prioritization provided by the tensor concept. Since the strengths of dependencies are also influential factors in the act of prioritization, The …
In-Field Failure Assessment Of Tractor Hydraulic System Operation Viapseudospectrum Of Acoustic Measurements, Saurabh Gupta, Mahdi Khosravy, Neeraj Gupta, Hemand Darbari
In-Field Failure Assessment Of Tractor Hydraulic System Operation Viapseudospectrum Of Acoustic Measurements, Saurabh Gupta, Mahdi Khosravy, Neeraj Gupta, Hemand Darbari
Turkish Journal of Electrical Engineering and Computer Sciences
Hydrological working conditions are critical indicators for the maintenance of tractor mechanical systems. This research presents a pseudospectrum approach to analyze the particle pollution level of the hydraulic filter in its aging process and thus on-time prediction and diagnosis of weak or faulty conditions. The practical experiments of pseudospectrum analysis are performed on oil filter sound records. For mobile application purposes, besides deployment of advanced audio recording equipment, three popular brands of cell phones are used. The soundtracks are recorded in different incremental stages of fluid contamination by pollutive particles until being choked based on the ISO4406 standard. The pseudospectrum …
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.
Energy-Efficient Scheduling For Real-Time Tasks Using Dynamic Slack Reclamation, Vasanthamani Kannaian, Visalakshi Palanisamy
Energy-Efficient Scheduling For Real-Time Tasks Using Dynamic Slack Reclamation, Vasanthamani Kannaian, Visalakshi Palanisamy
Turkish Journal of Electrical Engineering and Computer Sciences
The application domains of portable embedded real-time systems range from safety-critical applications like electronic control units in the automotive sector to entertainment applications like digital cameras and setup boxes in the consumer electronics sector. These systems attract users with multiple and sophisticated functionalities in a single system. The developments in VLSI technology have enabled IC manufacturers to incorporate more features in a single die, which facilitates these multipurpose systems. The increase in features and functionalities has a direct impact on power consumption and has to be strictly accounted for in the design of these embedded systems. The possibility of achieving …
Patient Comfort Level Prediction During Transport Using Artificial Neural Network, Zeljko Jovanovic, Marija Blagojevic, Dragan Jankovic, Aleksandar Peulic
Patient Comfort Level Prediction During Transport Using Artificial Neural Network, Zeljko Jovanovic, Marija Blagojevic, Dragan Jankovic, Aleksandar Peulic
Turkish Journal of Electrical Engineering and Computer Sciences
Since patient comfort during transport is a matter of paramount importance, this paper aims to determine the possibilities of applying neural networks for its prediction and monitoring. Specific objectives of the research include monitoring and predicting patient transport comfort, with subjective assessment of comfort by medical personnel. An original Android application that collects signals from an accelerometer and a GPS sensor was used with the aim of achieving the research goals. The collected signals were processed and a total of twelve parameters were calculated. A multilayer perceptron was created in the proposed research. The evaluation results indicate acceptable accuracy and …
Toxicity Prediction Of Small Drug Molecules Of Aryl Hydrocarbon Receptor Using Aproposed Ensemble Model, Vishan Kumar Gupta, Prashant Singh Rana
Toxicity Prediction Of Small Drug Molecules Of Aryl Hydrocarbon Receptor Using Aproposed Ensemble Model, Vishan Kumar Gupta, Prashant Singh Rana
Turkish Journal of Electrical Engineering and Computer Sciences
Quantitative structure-activity relationships and quantitative structure?property relationships have proved their usefulness for predicting toxicities of drug molecules regarding their biological activities. In silico toxicity prediction techniques are essential for reducing testing on rodents (in vivo) and for a less time-consuming and more cost-efficient alternative for the identification of toxic effects at an early stage of drug development. The authors aim to build a prediction model for better assessment of toxicity to quickly and efficiently test whether certain chemical compounds have the potential to disrupt the processes in the human body that may adversely affect human health. Here, we have proposed …
Pv-Based Off-Board Electric Vehicle Battery Charger Using Bidc, Ankita Paul, Krithiga Subramanian, Sujitha N
Pv-Based Off-Board Electric Vehicle Battery Charger Using Bidc, Ankita Paul, Krithiga Subramanian, Sujitha N
Turkish Journal of Electrical Engineering and Computer Sciences
In recent years, the use of renewable energy sources is increasing drastically in several sectors, which leads to its role in the automobile industry to charge electric vehicle (EV) batteries. In this paper, a photovoltaic (PV) array-fed off-board battery charging system using a bidirectional interleaved DC-DC converter (BIDC) is proposed for light-weight EVs. This off-board charging system is capable of operating in dual mode, thereby supplying power to the EV battery from the PV array in standstill conditions and driving the DC load by the EV battery during running conditions. This dual mode operation is accomplished by the use of …
Transmission Expansion Planning Based On A Hybrid Genetic Algorithm Approachunder Uncertainty, Ercan Şenyi̇ği̇t, Selçuk Mutlu, Bi̇lal Babayi̇ği̇t
Transmission Expansion Planning Based On A Hybrid Genetic Algorithm Approachunder Uncertainty, Ercan Şenyi̇ği̇t, Selçuk Mutlu, Bi̇lal Babayi̇ği̇t
Turkish Journal of Electrical Engineering and Computer Sciences
Transmission expansion planning (TEP) is one of the key decisions in power systems. Its impact on the system?s operation is excessive and long-lived. The aim of TEP is to determine new transmission lines effectively for a current transmission grid to fulfill the model objectives. However, to obtain a solution, especially under uncertainty, is extremely difficult due to the nonlinear mixed-integer structure of the TEP problem. In this paper, first genetic algorithm (GA) approaches for TEP are reviewed in the literature and then a new hybrid GA with linear modeling is proposed. The proposed GA method has a flexible structure and …
Design Of Energy Recovery Systems: Thermoelectric Combi Boiler Generator Andpower Analysis, Abdullah Hakan Yavuz
Design Of Energy Recovery Systems: Thermoelectric Combi Boiler Generator Andpower Analysis, Abdullah Hakan Yavuz
Turkish Journal of Electrical Engineering and Computer Sciences
Gas-fired combi boilers are commonly used to meet the need for heating and general-purpose hot water in developing countries. In this study, a thermoelectric combi boiler generator (TECBG) was developed. When the boiler is operated, cold water flows through the cold surface of TECBG and enters the boiler. In the same way, it is used by flows through the hot surface of TECBG in heated water. Thus, temperature difference occurrs between the surfaces of TECBG. The temperature difference is converted into electrical energy by Seebeck effect. The proposed system was implemented on a domestic combi boiler. The maximum temperature difference …
A Control Scheme For Maximizing The Delivered Power To The Load In A Standalonewind Energy Conversion System, Saeed Heshmatian, Davood A. Khaburi, Mahyar Khosravi, Ahad Kazemi
A Control Scheme For Maximizing The Delivered Power To The Load In A Standalonewind Energy Conversion System, Saeed Heshmatian, Davood A. Khaburi, Mahyar Khosravi, Ahad Kazemi
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper, a control scheme is proposed for maximum power point tracking (MPPT) in a variable speed standalone wind energy conversion system (WECS) with permanent magnet synchronous generator. A MPPT algorithm is designed trying to eliminate the main deficiency of the conventional perturbation and observation (P&O) method, which is the challenge of choosing a proper step size and the unwanted trade-off between accuracy and speed. The designed algorithm properly addresses this drawback and significantly improves the MPPT performance. Another important issue is to ensure fast and accurate tracking of the optimal reference point obtained from the MPPT algorithm and …
Performance Enhancement Of Photovoltaic System Using Genetic Algorithm- Based Maximum Power Point Tracking, Brammanayagam Nagarani, Jothiswaroopan Nesamony
Performance Enhancement Of Photovoltaic System Using Genetic Algorithm- Based Maximum Power Point Tracking, Brammanayagam Nagarani, Jothiswaroopan Nesamony
Turkish Journal of Electrical Engineering and Computer Sciences
In recent years, enormous progress has been made on power generation using photovoltaic (PV) system. Solar power is one of the most promising renewable energy sources that is providing its benefit specifically in rural areas. With the increasing need for solar energy, it becomes necessary to extract maximum power from the PV array. The output power of the solar cells varies directly with the ambient temperature and Irradiation. Therefore, the challenge is to track maximum power from the PV array when environmental factors change. This paper focuses on increasing the efficiency of a PV array by incorporating artificial intelligence techniques. …