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Full-Text Articles in Physical Sciences and Mathematics
Block Size Optimization For Pow Consensus Algorithm Based Blockchainapplications By Using Whale Optimization Algorithm, Betül Aygün, Hi̇lal Arslan
Block Size Optimization For Pow Consensus Algorithm Based Blockchainapplications By Using Whale Optimization Algorithm, Betül Aygün, Hi̇lal Arslan
Turkish Journal of Electrical Engineering and Computer Sciences
Blockchain-based applications come up with cryptocurrencies, especially Bitcoin, introducing a distributed ledger technologies for peer-to-peer networks and essentially records the transactions in blocks containing hash value of the previous blocks. Block generation constitutes the basis of this technology, and the optimization of such systems is among the most crucial concerns. Determining either the block size or the number of transactions in the block brings out a remarkable problem that has been solved by the miners in recent years. First, higher block size results in higher transaction time, on the other hand, smaller block size has many disadvantages such as security, …
A Novel Optimum Pi Controller Design Based On Stability Boundary Locussupported Particle Swarm Optimization In Avr System, Mahmut Temel Özdemi̇r
A Novel Optimum Pi Controller Design Based On Stability Boundary Locussupported Particle Swarm Optimization In Avr System, Mahmut Temel Özdemi̇r
Turkish Journal of Electrical Engineering and Computer Sciences
This study proposes a new approach that combines stability and optimization in the design of proportional? integral (PI) controller of automatic voltage regulators (AVR) of synchronous generators with variable system parameters. Thanks to this approach, a PI controller, providing the desired performance and the stability of the AVR system, has been designed. The approach follows a method investigating the PI gain values to achieve the desired goals. In the first step of the study, a new stability boundary locus is calculated for the case in which AVR system?s parameters have changed. The stability boundary locus (SBL) method is a graphic-based …
Adaptation Of Metaheuristic Algorithms To Improve Training Performance Of Aneszsl Model, Şi̇fa Özsari, Mehmet Serdar Güzel, Gazi̇ Erkan Bostanci, Ayhan Aydin
Adaptation Of Metaheuristic Algorithms To Improve Training Performance Of Aneszsl Model, Şi̇fa Özsari, Mehmet Serdar Güzel, Gazi̇ Erkan Bostanci, Ayhan Aydin
Turkish Journal of Electrical Engineering and Computer Sciences
Zero-shot learning (ZSL) is a recent promising learning approach that is similar to human vision systems. ZSL essentially allows machines to categorize objects without requiring labeled training data. In principle, ZSL proposes a novel recognition model by specifying merely the attributes of the category. Recently, several sophisticated approaches have been introduced to address the challenges regarding this problem. Embarrassingly simple approach to zeroshot learning (ESZSL) is one of the critical of those approaches that basically proposes a simple but efficient linear code solution. However, the performance of the ESZSL model mainly depends on parameter selection. Metaheuristic algorithms are considered as …
Joint Modeling Of Rayleigh Wave Dispersion And H/V Spectral Ratio Using Pareto-Basedmultiobjective Particle Swarm Optimization, Ersi̇n Büyük, Ekrem Zor, Abdullah Karaman
Joint Modeling Of Rayleigh Wave Dispersion And H/V Spectral Ratio Using Pareto-Basedmultiobjective Particle Swarm Optimization, Ersi̇n Büyük, Ekrem Zor, Abdullah Karaman
Turkish Journal of Earth Sciences
Estimating the shear wave velocity and thickness of geologic units in a sedimentary structure is important for quantifying the local site effect caused by an earthquake. Inversion of the Rayleigh wave dispersion alone is sensitive to the absolute average shear wave velocity, while the H/V spectral ratio is sensitive to velocity contrasts. The solution of these models in a joint system using conventional inversion techniques suffers from difficulties while evaluating partial derivatives, dependencies to the initial model that is sometimes difficult to estimate, and trapping at a local minimum. Herein, a joint model using the Pareto optimality technique with multiobjective …
A Hybrid Model Based On The Convolutional Neural Network Model And Artificial Bee Colony Or Particle Swarm Optimization-Based Iterative Thresholding For The Detection Of Bruised Apples, Mahmut Heki̇m, Onur Cömert, Kemal Adem
A Hybrid Model Based On The Convolutional Neural Network Model And Artificial Bee Colony Or Particle Swarm Optimization-Based Iterative Thresholding For The Detection Of Bruised Apples, Mahmut Heki̇m, Onur Cömert, Kemal Adem
Turkish Journal of Electrical Engineering and Computer Sciences
In this study, apple images taken with near-infrared (NIR) cameras were classified as bruised and healthy objects using iterative thresholding approaches based on artificial bee colony (ABC) and particle swarm optimization (PSO) algorithms supported by a convolutional neural network (CNN) deep learning model. The proposed model includes the following stages: image acquisition, image preprocessing, the segmentation of anatomical regions (stem-calyx regions) to be discarded, the detection of bruised areas on the apple images, and their classification. For this aim, by using the image acquisition platform with a NIR camera, a total of 1200 images at 6 different angles were taken …
Robust Optimal Operation Of Smart Distribution Grids With Renewable Basedgenerators, Omid Zare, Sadjad Galvani, Murtaza Farsadi
Robust Optimal Operation Of Smart Distribution Grids With Renewable Basedgenerators, Omid Zare, Sadjad Galvani, Murtaza Farsadi
Turkish Journal of Electrical Engineering and Computer Sciences
Modern distribution systems are equipped with various distributed energy resources (DERs) because of the importance of local generation. These distribution systems encounter more and more uncertainties because of the ever-increasing use of renewable energies. Other sources of uncertainty, such as load variation and system components? failure, will intensify the unpredictable nature of modern distribution systems. Integrating energy storage systems into distribution grids can play a role as a flexible bidirectional source to accommodate issues from constantly varying loads and renewable resources. The overall functionality of these modern distribution systems is enhanced using communication and computational abilities in smart grid frameworks. …
Ingan/Gan Tandem Solar Cell Parameter Estimation: A Comparative Stud, Abdelmoumene Benayad, Smail Berrah
Ingan/Gan Tandem Solar Cell Parameter Estimation: A Comparative Stud, Abdelmoumene Benayad, Smail Berrah
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper, two hybrid estimation approaches, hybrid genetic algorithm (TR-GA) and hybrid particle swarm optimization (TR-PSO), are used to estimate single-diode model InGaN/GaN solar cell parameters from J?V experimental data under AM0 illumination. These parameters are photocurrent density ($J_{ph}$), reverse saturation current density ($J_{s}$), ideality factor ($A$), series resistance ($R_{s}$), and shunt resistance ($R_{sh}$). The trust region (TR) method used in both approaches provides the initial conditions and helps to avoid the problem of premature convergence (due to local minimum). Simulation results based on the minimization of the mean square error between experimental and theoretical J-V characteristics show that …
Performance Comparison Of Optimization Algorithms In Lqr Controller Design For A Nonlinear System, Ümi̇t Önen, Abdullah Çakan, İlhan İlhan
Performance Comparison Of Optimization Algorithms In Lqr Controller Design For A Nonlinear System, Ümi̇t Önen, Abdullah Çakan, İlhan İlhan
Turkish Journal of Electrical Engineering and Computer Sciences
The development and improvement of control techniques has attracted many researchers for many years. Especially in the controller design of complex and nonlinear systems, various methods have been proposed to determine the ideal control parameters. One of the most common and effective of these methods is determining the controller parameters with optimization algorithms.In this study, LQR controller design was implemented for position control of the double inverted pendulum system on a cart. First of all, the equations of motion of the inverted pendulum system were obtained by using Lagrange formulation. These equations were linearized by Taylor series expansion around the …
Automatic Generation Control Analysis Of Power System With Nonlinearities Andelectric Vehicle Aggregators With Time-Varying Delay Implementing A Novel Control Strategy, Nimai Charan Patel, Binod Kumar Sahu, Manoj Kumar Debnath
Automatic Generation Control Analysis Of Power System With Nonlinearities Andelectric Vehicle Aggregators With Time-Varying Delay Implementing A Novel Control Strategy, Nimai Charan Patel, Binod Kumar Sahu, Manoj Kumar Debnath
Turkish Journal of Electrical Engineering and Computer Sciences
Automatic generation control (AGC) also known as load frequency control plays a vital role in interconnected power system for frequency regulation. Electric vehicles (EVs) with battery as the storage device can participate in frequency regulation service. In practice, a large number of EVs are aggregated as a single unit called EV aggregator for participation in frequency regulation service in AGC system. Participation of EV aggregators in AGC system for frequency regulation will be encouraged in near future because EVs have less environmental pollution than the conventional vehicles. However, participation of EV aggregators in AGC system may introduce time delay which …
Parameter Estimations From Gravity And Magnetic Anomalies Due To Deep-Seated Faults:Differential Evolution Versus Particle Swarm Optimization, Yunus Levent Eki̇nci̇, Çağlayan Balkaya, Gökhan Göktürkler
Parameter Estimations From Gravity And Magnetic Anomalies Due To Deep-Seated Faults:Differential Evolution Versus Particle Swarm Optimization, Yunus Levent Eki̇nci̇, Çağlayan Balkaya, Gökhan Göktürkler
Turkish Journal of Earth Sciences
Estimation of causative source parameters is an essential tool in exploration geophysics and is frequently applied using potential field datasets. Naturally inspired metaheuristic optimization algorithms based on some stochastic procedures have attracted more attention during the last decade due to their capability in finding the optimal solution of the model parameters from the parameter space via direct search routines. In this study, the solutions obtained through differential evolution algorithm, a rarely used metaheuristic algorithm in geophysics, and particle swarm optimization, which is one of the most used global optimization algorithms in geophysics, have been compared in terms of robustness, consistency, …
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 …
Available Transfer Capability Enhancement With Facts Using Hybrid Pi-Pso, Abubakar Sadiq Ahmad, Sunusi Sani Adamu, Muhammad Buhari
Available Transfer Capability Enhancement With Facts Using Hybrid Pi-Pso, Abubakar Sadiq Ahmad, Sunusi Sani Adamu, Muhammad Buhari
Turkish Journal of Electrical Engineering and Computer Sciences
In deregulation, growth in electrical loads necessitates improving power delivery, while nondiscriminatory access to transmission grid is a requirement. Deregulation causes a significant rise in transactions, which requires adequate transfer capability to secure economic transactions. In sustainable power delivery, FACTS devices are deployed to enhance available transfer capability (ATC). However, the high investment cost of FACTS makes the problem formulation a multiobjective optimization: power transfer maximization and minimization of FACTS sizes. Furthermore, due to the complexity in optimizing the control variables of voltage source converter types of FACTS, often the solution results in local optima and high computational time. This …
A Novel Perturbed Particle Swarm Optimization-Based Support Vector Machine Forfault Diagnosis In Power Distribution Systems, Hoang Thi Thom, Cho Ming-Yuan, Vu Quoc Tuan
A Novel Perturbed Particle Swarm Optimization-Based Support Vector Machine Forfault Diagnosis In Power Distribution Systems, Hoang Thi Thom, Cho Ming-Yuan, Vu Quoc Tuan
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper, a novel perturbed particle swarm optimization (PPSO) algorithm is investigated to improve the performance of a support vector machine (SVM) for short-circuit fault diagnosis in power distribution systems. In the proposed PPSO algorithm, the velocity of each particle is perturbed whenever the particles strike into a local optimum, in order to achieve a higher quality solution to optimization problems. Furthermore, the concept of proposed perturbation is applied to three variants of PSO, and improved corresponding algorithms are named perturbed C-PSO (PC-PSO), perturbed T-PSO (PT-PSO), and perturbed K-PSO (PK-PSO). For the purpose of fault diagnosis, the time- domain …
Two-Area Load Frequency Control With Redox Ow Battery Using Intelligentalgorithms In A Restructured Scenario, Lakshmi Dhandapani, Fathima Peer, Ranganath Muthu
Two-Area Load Frequency Control With Redox Ow Battery Using Intelligentalgorithms In A Restructured Scenario, Lakshmi Dhandapani, Fathima Peer, Ranganath Muthu
Turkish Journal of Electrical Engineering and Computer Sciences
Load frequency control (LFC) is an essential aspect of power system dynamics. This paper focuses on the optimization of LFC for a two-area deregulated power system under different scenarios. A recent nature-inspired ower pollination algorithm (FPA), based on the pollination process of plants, is used to tune the proportional integral (PI) controller parameters of LFC for the global minima solution. FPA is compared with a genetic algorithm, particle swarm optimization, and a conventional PI controller. During large load disturbance in the areas, controllers are incapable of reducing frequency deviations and tie-line power oscillations due to the slow response of the …
An Efficient Recurrent Fuzzy Cmac Model Based On A Dynamic-Group--Based Hybrid Evolutionary Algorithm For Identification And Prediction Applications, Chin-Ling Lee, Chengjian Lin
An Efficient Recurrent Fuzzy Cmac Model Based On A Dynamic-Group--Based Hybrid Evolutionary Algorithm For Identification And Prediction Applications, Chin-Ling Lee, Chengjian Lin
Turkish Journal of Electrical Engineering and Computer Sciences
This article presents an efficient TSK-type recurrent fuzzy cerebellar model articulation controller (T-RFCMAC) model based on a dynamic-group--based hybrid evolutionary algorithm (DGHEA) for solving identification and prediction problems. The proposed T-RFCMAC model is based on the traditional CMAC model and the Takagi--Sugeno--Kang (TSK) parametric fuzzy inference system. Otherwise, the recurrent network, which imports feedback links with a receptive field cell, is embedded in the T-RFCMAC model, and the feedback units are used as memory elements. The DGHEA, which is a hybrid of the dynamic-group quantum particle swarm optimization (QPSO) and the Nelder--Mead method, is proposed for adjusting the parameters of …
Adaptive Collaborative Speed Control Of Pmdc Motor Using Hyperbolic Secant Functions And Particle Swarm Optimization, Omer Saleem, Khalid Mahmood-Ul-Hasan
Adaptive Collaborative Speed Control Of Pmdc Motor Using Hyperbolic Secant Functions And Particle Swarm Optimization, Omer Saleem, Khalid Mahmood-Ul-Hasan
Turkish Journal of Electrical Engineering and Computer Sciences
This paper presents an adaptive collaborative speed controller for a permanent magnet direct-current (PMDC) motor. The proposed scheme beneficially combines the control efforts of a proportional-integral (PI) controller and a linear-quadratic regulator (LQR) via a weighted summing module. Initially, the weightages of the summing module are kept fixed. They are optimally tuned and tested via the particle swarm optimization algorithm. In order to synergize the controller combination, these weightages are adaptively modulated as well, using hyperbolic secant functions of the error dynamics of the motor's angular speed. The adaptive combination renders significant enhancement in the transient response, steady-state response, input-energy …
Modeling And Control Of A Permanent-Magnet Brushless Dc Motor Drive Using A Fractional Order Proportional-Integral-Derivative Controller, Swapnil Khubalkar, Anjali Junghare, Mohan Aware, Shantanu Das
Modeling And Control Of A Permanent-Magnet Brushless Dc Motor Drive Using A Fractional Order Proportional-Integral-Derivative Controller, Swapnil Khubalkar, Anjali Junghare, Mohan Aware, Shantanu Das
Turkish Journal of Electrical Engineering and Computer Sciences
This paper deals with the speed control of a permanent-magnet brushless direct current (PMBLDC) motor. A fractional order PID (FOPID) controller is used in place of the conventional PID controller. The FOPID controller is a generalized form of the PID controller in which the order of integration and differentiation is any real number. It is shown that the proposed controller provides a powerful framework to control the PMBLDC motor. Parameters of the controller are found by using a novel dynamic particle swarm optimization (dPSO) method. The frequency domain pole-zero (p-z) interlacing method is used to approximate the fractional order operator. …
An Intelligent Pso-Based Energy Efficient Load Balancing Multipath Technique In Wireless Sensor Networks, Sukhchandan Randhawa, Sushma Jain
An Intelligent Pso-Based Energy Efficient Load Balancing Multipath Technique In Wireless Sensor Networks, Sukhchandan Randhawa, Sushma Jain
Turkish Journal of Electrical Engineering and Computer Sciences
To provide a reliable and efficient service, load balancing plays an important role in wireless sensor networks (WSNs). There is a need to maximize the network lifetime for WSNs applications with periodic generation of data. Due to the relationship between energy consumption and network sensor node lifetime, energy consumption in a network should be minimized and balanced in order to increase network lifetime. Energy-efficient load-balancing techniques are needed to solve this problem. In this paper, a particle swarm optimization (PSO)-based energy-efficient load-balancing technique is proposed, in which the required number of routing paths and energy consumption of different nodes and …
Time-Jerk Optimal Trajectory Planning Of A 7-Dof Redundant Robot, Shaotian Lu, Jingdong Zhao, Li Jiang, Hong Liu
Time-Jerk Optimal Trajectory Planning Of A 7-Dof Redundant Robot, Shaotian Lu, Jingdong Zhao, Li Jiang, Hong Liu
Turkish Journal of Electrical Engineering and Computer Sciences
In order to improve the efficiency and smoothness of a robot and reduce its vibration, an algorithm called the augmented Lagrange constrained particle swarm optimization (ALCPSO), which combines constrained particle swarm optimization with the augmented Lagrange multiplier method to realize time-jerk (defined as the derivative of the acceleration) optimal trajectory planning is proposed. Kinematic constraints such as joint velocities, accelerations, jerks, and traveling time are considered. The ALCPSO algorithm is used to avoid local optimization because a new particle swarm is newly produced at each initial time process. Additionally, the best value obtained from the former generation is saved and …
Optimal Siting And Sizing Of Rapid Charging Station For Electric Vehicles Considering Bangi City Road Network In Malaysia, Mainul Islam, Hussain Shareef, Azah Mohamed
Optimal Siting And Sizing Of Rapid Charging Station For Electric Vehicles Considering Bangi City Road Network In Malaysia, Mainul Islam, Hussain Shareef, Azah Mohamed
Turkish Journal of Electrical Engineering and Computer Sciences
Recently, electric vehicles (EVs) have been seen as a felicitous option towards a less carbon-intensive road transport. The key issue in this system is recharging the EV batteries before they are exhausted. Thus, charging stations (CSs) should be carefully located to make sure EV users can access a CS within their driving range. Considering geographic information and traffic density, this paper proposes an optimization overture for optimal siting and sizing of a rapid CS (RCS). It aims to minimize the daily total cost (which includes the cost of substation energy loss, traveling cost of EVs to the CS, and investment, …
Applying Metaheuristic Optimization Methods To Design Novel Adaptive Pi-Type Fuzzy Logic Controllers For Load-Frequency Control In A Large-Scale Power Grid, Thimaiphuong Dao, Yaonan Wang, Ngockhoat Nguyen
Applying Metaheuristic Optimization Methods To Design Novel Adaptive Pi-Type Fuzzy Logic Controllers For Load-Frequency Control In A Large-Scale Power Grid, Thimaiphuong Dao, Yaonan Wang, Ngockhoat Nguyen
Turkish Journal of Electrical Engineering and Computer Sciences
Due to the complexity and diversity of large-scale power systems in practice, designing load-frequency control (LFC) strategies against load variations faces big challenges to ensure the stability and economy of the network. The focus of this paper is to design a novel adaptive PI-type fuzzy logic (FL)-based LFC architecture for solving the LFC problem in such an interconnected electric power grid. Applying 2 biologically inspired optimization methods, namely particle swarm optimization method and a genetic algorithm, the membership functions and rule base of a basic PI-type FL model were parameterized and optimized simultaneously and successfully. An online self-tuning method was …
Fuzzy Pso-Based Algorithm For Controlling Base Station Movements In A Wireless Sensor Network, Moosa Ayati, Mahdi Pasha Zanousi
Fuzzy Pso-Based Algorithm For Controlling Base Station Movements In A Wireless Sensor Network, Moosa Ayati, Mahdi Pasha Zanousi
Turkish Journal of Electrical Engineering and Computer Sciences
There are strong limitations on the software, energy, and hardware capacities of a wireless sensor network (WSN) and therefore algorithms that increase the lifetime of a WSN are of great significance. In this paper, a mobile base station movement control strategy for WSNs is proposed. This strategy combines fuzzy logic node clustering, fuzzy cluster-head selection, and fuzzy logic control (FLC) of the base station movements. After determining cluster-heads, according to the distance and energy of the heads, the base station moves on a predefined square, triangle, circle, or hexagon shaped path. Direction and speed of the movements are controlled by …
The Parallel Resonance Impedance Detection Method For Parameter Estimation Of Power Line And Transformer By Using Csa, Ga, And Pso, Bahadir Akbal, Abdullah Ürkmez
The Parallel Resonance Impedance Detection Method For Parameter Estimation Of Power Line And Transformer By Using Csa, Ga, And Pso, Bahadir Akbal, Abdullah Ürkmez
Turkish Journal of Electrical Engineering and Computer Sciences
Power line parameters are an important factor in relay applications and power quality studies. In the literature, the phasor measurement unit method and measuring of current and voltage at two ends of the power line were usually used to estimate the power line parameters. In this study, the parallel resonance impedance detection method was used to estimate the power line parameter to obtain input data. The real measurement values are used to obtain parallel resonance impedance in this method. The real measurement values include the measurement errors of the current and voltage transformer. Thus, the estimated parameter values are realistic. …
Lifetime Maximization Of Wireless Sensor Networks Using Particle Swarm Optimization, Aleem Kabeer Mir, Muhammad Zubair, Ijaz Mansoor Qureshi
Lifetime Maximization Of Wireless Sensor Networks Using Particle Swarm Optimization, Aleem Kabeer Mir, Muhammad Zubair, Ijaz Mansoor Qureshi
Turkish Journal of Electrical Engineering and Computer Sciences
Wireless sensor networks have multiple applications in intelligent environment and structural monitoring. The major challenge in wireless sensor networks is the power constraint. This paper deals with minimizing the energy utilization of wireless sensor nodes and maximizing their overall life span. The objective of our proposed scheme is to find a method for grouping sensors into the maximum number of distinct sensor cover sets to totally monitor the required area. This problem can be solved by using the disjoint cover set problem. Present optimization techniques take much time and deliver unsatisfactory results in large-scale networks. This paper proposes a technique …
Site-Specific Design Optimization Of Horizontal-Axis Wind Turbine Systems Using Pso Algorithm, Ulaş Emi̇noğlu
Site-Specific Design Optimization Of Horizontal-Axis Wind Turbine Systems Using Pso Algorithm, Ulaş Emi̇noğlu
Turkish Journal of Electrical Engineering and Computer Sciences
Due to the complexity of wind turbine systems (WTSs) containing multiple components, design parameters of a WTS must match each other in order to produce electrical energy at a lower cost and a higher efficiency. In this study, a framework for site-specific design optimization of a horizontal-axis WTS is proposed. It is based on cost reduction and the objective function is the produced energy cost. The cost of energy model proposed by the National Renewable Energy Laboratory is utilized. In order to compute turbine output power that results in annual energy production, a new approach is proposed to model the …
Optimal Power Flow By Considering System Security Cost And Small Signal Stability Constraints, Mohammad Sarvi, Mohammad Reza Salimian
Optimal Power Flow By Considering System Security Cost And Small Signal Stability Constraints, Mohammad Sarvi, Mohammad Reza Salimian
Turkish Journal of Electrical Engineering and Computer Sciences
The main objective of optimal power flow is to find the proper operating point for the power system. In this paper, the optimal power flow by considering system security cost (OPFSC) and the small signal stability constraint is presented. For this purpose, the total profit of the system by considering the system constraints is optimized. The total profit of the system is equal to the combination of profit from the active power consumption, active power generation cost, and system security cost. System security cost includes the cost of load shedding, which is computed for all contingencies that may occur in …
Energy Optimization In Wireless Sensor Networks Using A Hybrid K-Means Pso Clustering Algorithm, Basma Solaiman
Energy Optimization In Wireless Sensor Networks Using A Hybrid K-Means Pso Clustering Algorithm, Basma Solaiman
Turkish Journal of Electrical Engineering and Computer Sciences
No abstract provided.
Bbo Algorithm-Based Tuning Of Pid Controller For Speed Control Of Synchronous Machine, Gowrishankar Kasilingam, Jagadeesh Pasupuleti
Bbo Algorithm-Based Tuning Of Pid Controller For Speed Control Of Synchronous Machine, Gowrishankar Kasilingam, Jagadeesh Pasupuleti
Turkish Journal of Electrical Engineering and Computer Sciences
No abstract provided.
Heuristic Methods For Postoutage Voltage Magnitude Calculations, Oğuzhan Ceylan, Aydoğan Özdemi̇r, Hasan Dağ
Heuristic Methods For Postoutage Voltage Magnitude Calculations, Oğuzhan Ceylan, Aydoğan Özdemi̇r, Hasan Dağ
Turkish Journal of Electrical Engineering and Computer Sciences
Power systems play a significant role in every aspect of our daily lives. Hence, their continuation without any interruption (or with the least duration of interruption due to faults or scheduled maintenances) is one of the key aims of electrical energy providers. As a result, electrical energy providers need to check in great detail the integrity of their power systems by performing regular contingency studies of the equipment involved. Among others, line and transformer outage simulations constitute an integral part of an electrical management system. Both accuracy and calculation speed depend on the branch outage model and/or the solution algorithms …
A Generalized Particle Swarm Optimization Using Reverse Direction Information, Emre Çomak
A Generalized Particle Swarm Optimization Using Reverse Direction Information, Emre Çomak
Turkish Journal of Electrical Engineering and Computer Sciences
In this study, an improved particle swarm optimization (PSO) algorithm, including 4 types of new velocity updating formulae (each is equal to the traditional PSO), was introduced. This algorithm was called the reverse direction supported particle swarm optimization (RDS-PSO) algorithm. The RDS-PSO algorithm has the potential to extend the diversity and generalization of traditional PSO by regulating the reverse direction information adaptively. To implement this extension, 2 new constants were added to the velocity update equation of the traditional PSO, and these constants were regulated through 2 alternative procedures, i.e. max--min-based and cosine amplitude-based diversity-evaluating procedures. The 4 most commonly …