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Full-Text Articles in Physical Sciences and Mathematics
A Novel Method Of Relieving Congestion In Hybrid Deregulated Market Utilizing Renewable Energy Sources, Joseph Jeslin Drusila Nesamalar, Paramasivam Venkatesh, Sathiasamuel Charles Raja
A Novel Method Of Relieving Congestion In Hybrid Deregulated Market Utilizing Renewable Energy Sources, Joseph Jeslin Drusila Nesamalar, Paramasivam Venkatesh, Sathiasamuel Charles Raja
Turkish Journal of Electrical Engineering and Computer Sciences
No abstract provided.
Speech Recognition Using Ann And Predator-Influenced Civilized Swarm Optimization Algorithm, Teena Mittal, Rajendra Kumar Sharma
Speech Recognition Using Ann And Predator-Influenced Civilized Swarm Optimization Algorithm, Teena Mittal, Rajendra Kumar Sharma
Turkish Journal of Electrical Engineering and Computer Sciences
This paper proposes a hybrid optimization technique, predator-influenced civilized swarm optimization, by integrating civilized swarm optimization (CSO) and predator-prey optimization (PPO) techniques. CSO is the integration of the attributes of particle swarm optimization and a society civilization algorithm (SCA). In the SCA, the swarm is divided into a few societies, and each society has its own society leader (SL); other individuals of the society are termed society members. The combination of all such societies forms a civilization, and the best-performing SL becomes the civilization leader (CL). In CSO, SLs and members update their positions through the guidance of their own …
Bull Optimization Algorithm Based On Genetic Operators For Continuous Optimization Problems, Oğuz Findik
Bull Optimization Algorithm Based On Genetic Operators For Continuous Optimization Problems, Oğuz Findik
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper, the researcher proposes a new evolutionary optimization algorithm that depends on genetic operators such as crossover and mutation, referred to as the bull optimization algorithm (BOA). This new optimization algorithm is called the BOA because the best individual is used to produce offspring individuals. The selection algorithm used in the genetic algorithm (GA) is removed from the proposed algorithm. Instead of the selection algorithm, individuals initially produced attempt to achieve better individuals. In the proposed method, crossover operation is always performed by using the best individual. The mutation process is carried out by using individual positions. In …
Epilepsy Diagnosis Using Artificial Neural Network Learned By Pso, Nesi̇be Yalçin, Gülay Tezel, Ci̇han Karakuzu
Epilepsy Diagnosis Using Artificial Neural Network Learned By Pso, Nesi̇be Yalçin, Gülay Tezel, Ci̇han Karakuzu
Turkish Journal of Electrical Engineering and Computer Sciences
Electroencephalogram (EEG) is used routinely for diagnosis of diseases occurring in the brain. It is a very useful clinical tool in the classification of epileptic seizures and the diagnosis of epilepsy. In this study, epilepsy diagnosis has been investigated using EEG records. For this purpose, an artificial neural network (ANN), widely used and known as an active classification technique, is applied. The particle swarm optimization (PSO) method, which does not need gradient calculation, derivative information, or any solution of differential equations, is preferred as the training algorithm for the ANN. A PSO-based neural network (PSONN) model is diversified according to …
Modified Particle Swarm Optimization For Economic-Emission Load Dispatch Of Power System Operation, Mohd Noor Abdullah, Ab Halim Abu Bakar, Nasrudin Abd Rahim, Hazlie Mokhlis
Modified Particle Swarm Optimization For Economic-Emission Load Dispatch Of Power System Operation, Mohd Noor Abdullah, Ab Halim Abu Bakar, Nasrudin Abd Rahim, Hazlie Mokhlis
Turkish Journal of Electrical Engineering and Computer Sciences
This paper proposes a modified particle swarm optimization considering time-varying acceleration coefficients for the economic-emission load dispatch (EELD) problem. The new adaptive parameter is introduced to update the particle movements through the modification of the velocity equation of the classical particle swarm optimization (PSO) algorithm. The idea is to enhance the performance and robustness of classical PSO. The price penalty factor method is used to transform the multiobjective EELD problem into a single-objective problem. Then the weighted sum method is applied for finding the Pareto front solution. The best compromise solution for this problem is determined based on the fuzzy …
Shuffled Frog Leaping Algorithm Optimization For Ac--Dc Optimal Power Flow Dispatch, Abolfazl Rahiminejad, Arash Alimardani, Behrooz Vahidi, Seyed Hossein Hosseinian
Shuffled Frog Leaping Algorithm Optimization For Ac--Dc Optimal Power Flow Dispatch, Abolfazl Rahiminejad, Arash Alimardani, Behrooz Vahidi, Seyed Hossein Hosseinian
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper, a simple-implemented and reliable AC--DC optimal power flow (OPF) is proposed. Although high-voltage direct current (HVDC) transmission lines are being increasingly used in power systems, new optimization algorithms such as evolutionary and memetic algorithms, which never stick in local minimum, so far have not been implemented in the AC--DC OPF problem. An evolutionary algorithm known as the shuffled frog leaping algorithm (SFLA) is proposed in this paper to solve the OPF dispatch in an AC--DC power system (including both high-voltage alternating current and HVDC transmission lines). The implementation of the AC--DC OPF with these kinds of methods …
Comparative Learning Global Particle Swarm Optimization For Optimal Distributed Generations' Output, Jasrul Jamani Jamian, Hazlie Mokhlis, Mohd Wazir Mustafa, Mohd Noor Abdullah, Muhammad Ariff Baharuddin
Comparative Learning Global Particle Swarm Optimization For Optimal Distributed Generations' Output, Jasrul Jamani Jamian, Hazlie Mokhlis, Mohd Wazir Mustafa, Mohd Noor Abdullah, Muhammad Ariff Baharuddin
Turkish Journal of Electrical Engineering and Computer Sciences
The appropriate output of distributed generation (DG) in a distribution network is important for maximizing the benefit of the DG installation in the network. Therefore, most researchers have concentrated on the optimization technique to compute the optimal DG value. In this paper, the comparative learning in global particle swarm optimization (CLGPSO) method is introduced. The implementation of individual cognitive and social acceleration coefficient values for each particle and a new fourth term in the velocity formula make the process of convergence faster. This new algorithm is tested on 6 standard mathematical test functions and a 33-bus distribution system. The performance …
Induction Motor Parameter Estimation Using Metaheuristic Methods, Ali̇ İhsan Çanakoğlu, Asim Gökhan Yetgi̇n, Hasan Temurtaş, Mustafa Turan
Induction Motor Parameter Estimation Using Metaheuristic Methods, Ali̇ İhsan Çanakoğlu, Asim Gökhan Yetgi̇n, Hasan Temurtaş, Mustafa Turan
Turkish Journal of Electrical Engineering and Computer Sciences
The steady-state equivalent circuit parameters of an induction motor can be estimated using the operation characteristics that are provided by manufacturers. The characteristics of the motor used in estimation methods are the starting, maximum, and nominal torque values; the power factor; and efficiency. The operation characteristics of a motor given in data sheets are generally based on design parameters and are not suitable with real values. For this reason, in this paper, the data used in the parameter estimation for induction motors are taken from the literature. Using an optimization method for parameter estimation is useful for comparing the manufacturer …
A Comparative Study In Power Oscillation Damping By Statcom And Sssc Based On The Multiobjective Pso Algorithm, Ali Ajami, Mehdi Armaghan
A Comparative Study In Power Oscillation Damping By Statcom And Sssc Based On The Multiobjective Pso Algorithm, Ali Ajami, Mehdi Armaghan
Turkish Journal of Electrical Engineering and Computer Sciences
To improve the damping of power system oscillations by supplementary controller design for the static synchronous series compensator (SSSC) and static synchronous compensator (STATCOM), a multiobjective function based on the particle swarm optimization (PSO) algorithm for solving this optimization problem is introduced. The presented objective function includes the damping factor and the damping ratio of the lightly damped and undamped electromechanical modes. These controllers are adjusted to concurrently transfer the lightly damped and undamped electromechanical modes to a recommended region in the s-plane. For this purpose, the reduced linearized Phillips-Heffron model of the power system with a single machine and …
Symbol Detection Using The Differential Evolution Algorithm In Mimo-Ofdm Systems, Muhammet Nuri̇ Seyman, Necmi̇ Taşpinar
Symbol Detection Using The Differential Evolution Algorithm In Mimo-Ofdm Systems, Muhammet Nuri̇ Seyman, Necmi̇ Taşpinar
Turkish Journal of Electrical Engineering and Computer Sciences
Channel estimation and symbol detection in multiple-input and multiple-output (MIMO)-orthogonal frequency division multiplexing (OFDM) systems are essential tasks. Although the maximum likelihood (ML) detector reveals excellent performance for symbol detection, the computational complexity of this algorithm is extremely high in systems with more transmitter antennas and high-order constellation size. In this paper, we propose the differential evolution (DE) algorithm in order to reduce the search space of the ML detector and the computational complexity of symbol detection in MIMO-OFDM systems. The DE algorithm is also compared to some heuristic approaches, such as the genetic algorithm and particle swarm optimization. According …
Mitigation Of Ssr And Lfo With A Tcsc Based-Conventional Damping Controller Optimized By The Pso Algorithm And A Fuzzy Logic Controller, Hasan Gahramani, Akbar Lak, Murtaza Farsadi, Hossein Hosseini
Mitigation Of Ssr And Lfo With A Tcsc Based-Conventional Damping Controller Optimized By The Pso Algorithm And A Fuzzy Logic Controller, Hasan Gahramani, Akbar Lak, Murtaza Farsadi, Hossein Hosseini
Turkish Journal of Electrical Engineering and Computer Sciences
The subsynchronous resonance (SSR) phenomenon may occur when a steam turbine-generator is connected to a long transmission line with series compensation. Flexible AC transmission systems (FACTS) devices are widely applied to damp the SSR and low-frequency oscillation (LFO). A thyristor-controlled series capacitor (TCSC) is a commercially available FACTS device that was developed for damping the SSR and LFO. In this paper, 2 control methods for damping the SSR and LFO are added to the TCSC main controller in order to demonstrate that the SSR damping capability of the TCSC can be enhanced by proper modulation of the firing angle. The …
Bidding Strategy Of Generation Companies In A Competitive Electricity Market Using The Shuffled Frog Leaping Algorithm, Vijaya Kumar Jonnalagadda, Vinod Kumar Dulla Mallesham
Bidding Strategy Of Generation Companies In A Competitive Electricity Market Using The Shuffled Frog Leaping Algorithm, Vijaya Kumar Jonnalagadda, Vinod Kumar Dulla Mallesham
Turkish Journal of Electrical Engineering and Computer Sciences
In a competitive electricity market, generation companies need suitable bidding models to maximize their profit. Therefore, each supplier will bid strategically for choosing the bidding coefficients to counter the competitors' bidding strategies. In this paper, the optimal bidding strategy problem is solved using a novel algorithm based on the shuffled frog leaping algorithm (SFLA). It is a memetic metaheuristic that is designed to seek a global optimal solution by performing a heuristic search. It combines the benefits of the genetic-based memetic algorithm (MA) and the social behavior-based particle swarm optimization (PSO). This allows it to have a more precise search …
Ssr Mitigation With Sssc Thanks To Fuzzy Control, Seyed Mohammad Hassan Hosseini, Hadi Samadzadeh, Javad Olamaei, Murtaza Farsadi
Ssr Mitigation With Sssc Thanks To Fuzzy Control, Seyed Mohammad Hassan Hosseini, Hadi Samadzadeh, Javad Olamaei, Murtaza Farsadi
Turkish Journal of Electrical Engineering and Computer Sciences
This paper deals with the capability of a static synchronous series compensator (SSSC) to attenuate the subsynchronous resonance (SSR). Two well-known controllers are designed, namely a conventional damping controller (CDC) and fuzzy logic damping controller (FLDC). These 2 damping controllers are added to a main control loop of a SSSC operating as a SSR damping controller. It should be noted that, to optimize the parameters of the CDC, a versatile optimization technique is implemented, namely particle swarm optimization (PSO). A comprehensive comparison between the 2 control methods is carried out for different operational conditions. To observe the superior performance of …
An Improved Fastslam Framework Using Soft Computing, Ramazan Havangi, Mohammad Ali Nekoui, Mohammad Teshnehlab
An Improved Fastslam Framework Using Soft Computing, Ramazan Havangi, Mohammad Ali Nekoui, Mohammad Teshnehlab
Turkish Journal of Electrical Engineering and Computer Sciences
FastSLAM is a framework for simultaneous localization and mapping (SLAM) using a Rao-Blackwellized particle filter. However, FastSLAM degenerates over time. This degeneracy is due to the fact that a particle set estimating the pose of the robot loses its diversity. One of the main reasons for losing particle diversity in FastSLAM is sample impoverishment. In this case, most of the particle weights are insignificant. Another problem of FastSLAM relates to the design of an extended Kalman filter (EKF) for the landmark position's estimation. The performance of the EKF and the quality of the estimation depend heavily on correct a priori …
A Modified Particle Swarm Optimization Algorithm And Its Application To The Multiobjective Fet Modeling Problem, Ufuk Özkaya, Fi̇li̇z Güneş
A Modified Particle Swarm Optimization Algorithm And Its Application To The Multiobjective Fet Modeling Problem, Ufuk Özkaya, Fi̇li̇z Güneş
Turkish Journal of Electrical Engineering and Computer Sciences
This paper introduces a modified particle swarm algorithm to handle multiobjective optimization problems. In multiobjective PSO algorithms, the determination of Pareto optimal solutions depends directly on the strategy of assigning a best local guide to each particle. In this work, the PSO algorithm is modified to assign a best local guide to each particle by using minimum angular distance information. This algorithm is implemented to determine field-effect transistor (FET) model elements subject to the Pareto domination between the scattering parameters and operation bandwidth. Furthermore, the results are compared with those obtained by the nondominated sorting genetic algorithm-II. FET models are …
Multiobjective Fet Modeling Using Particle Swarm Optimization Based On Scattering Parameters With Pareto Optimal Analysis, Fi̇li̇z Güneş, Ufuk Özkaya
Multiobjective Fet Modeling Using Particle Swarm Optimization Based On Scattering Parameters With Pareto Optimal Analysis, Fi̇li̇z Güneş, Ufuk Özkaya
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper, design-oriented field effect transistor (FET) models are produced. For this purpose, FET modeling is put forward as a constrained, multiobjective optimization problem. Two novel methods for multiobjective optimization are employed: particle swarm optimization (PSO) uses the single-objective function, which gathers all of the objectives as aggregating functions; and the nondominated sorting genetic algorithm-II (NSGA-II) sorts all of the trade-off solutions on the Pareto frontiers. The PSO solution is compared with the Pareto optimum solutions in the biobjective plane and the success of the first method is verified. Furthermore, the resulting FET models are compared with similar FET …
Discrete Particle Swarm Optimization For The Team Orienteering Problem, Ai̇şe Zülal Şevkli̇, Fati̇h Erdoğan Sevi̇lgen
Discrete Particle Swarm Optimization For The Team Orienteering Problem, Ai̇şe Zülal Şevkli̇, Fati̇h Erdoğan Sevi̇lgen
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper, a novel discrete particle swarm optimization (PSO) algorithm is proposed to solve the team orienteering problem (TOP). Discrete evaluation is achieved by redefining all operators and operands used in PSO. To obtain better results, a strengthened PSO, which improves both exploration and exploitation during the search process, is employed. Our algorithm achieves the best known solutions in a short time compared to previous heuristics for the TOP.
A Novel And Efficient Algorithm For Adaptive Filtering: Artificial Bee Colony Algorithm, Nurhan Karaboğa, Mehmet Bahadir Çeti̇nkaya
A Novel And Efficient Algorithm For Adaptive Filtering: Artificial Bee Colony Algorithm, Nurhan Karaboğa, Mehmet Bahadir Çeti̇nkaya
Turkish Journal of Electrical Engineering and Computer Sciences
The uni-modal error surfaces and intrinsic stable behaviors of adaptive finite impulse response (FIR) filters make gradient based algorithms very effective in the design of these filters. Gradient based design methods are well developed for the design of adaptive FIR filters and widely applied to the distinct areas such as noise cancellation, system identification and channel equalization. However, the studies on adaptive infinite impulse response (IIR) filters are not as common as adaptive FIR filters since the stability during the adaptation process may not be ensured in some applications, and the convergence to the optimal design is not always guaranteed …
Sequence Alignment From The Perspective Of Stochastic Optimization: A Survey, İhsan Ömür Bucak, Volkan Uslan
Sequence Alignment From The Perspective Of Stochastic Optimization: A Survey, İhsan Ömür Bucak, Volkan Uslan
Turkish Journal of Electrical Engineering and Computer Sciences
DNA and protein are the fundamental biological sequences. DNA is a fundamental molecule that plays a vital role in the processes of life. Proteins synthesized by DNA in a cell are the building blocks of every living organism. There is a variety of reasons behind the alignment of biological sequences. Biological sequence alignment helps to discover functional and structural similarity of sequences. Biologists work with these aligned sequences to construct phylogenetic trees, characterize protein families, and predict protein structure. Sequence alignment is an extremely promising field of research that is characterized by very high computational complexity. Stochastic optimization is needed …
Performance Analysis Of Swarm Optimization Approaches For The Generalized Assignment Problem In Multi-Target Tracking Applications, Ali̇ Önder Bozdoğan, Asim Egemen Yilmaz, Murat Efe
Performance Analysis Of Swarm Optimization Approaches For The Generalized Assignment Problem In Multi-Target Tracking Applications, Ali̇ Önder Bozdoğan, Asim Egemen Yilmaz, Murat Efe
Turkish Journal of Electrical Engineering and Computer Sciences
The aim of this study is to investigate the suitability of selected swarm optimization algorithms to the generalized assignment problem as encountered in multi-target tracking applications. For this purpose, we have tested variants of particle swarm optimization and ant colony optimization algorithms to solve the 2D generalized assignment problem with simulated dense and sparse measurement/track matrices and compared their performance to that of the auction algorithm. We observed that, although with some modification swarm optimization algorithms provide improvement in terms of speed, they still fall behind the auction algorithm in finding the optimum solution to the problem. Among the investigated …
Stpso: Strengthened Particle Swarm Optimization, Ai̇şe Zülal Şevkli̇, Fati̇h Erdoğan Sevi̇lgen
Stpso: Strengthened Particle Swarm Optimization, Ai̇şe Zülal Şevkli̇, Fati̇h Erdoğan Sevi̇lgen
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper, we present a novel approach to strengthen Particle Swarm Optimization (PSO). PSO is a population-based metaheuristic that takes advantage of individual memory and social cooperation in a swarm. It has been applied to a variety of optimization problems because of its simplicity and fast convergence. However, straightforward application of PSO suffers from premature convergence and lack of intensification around the local best locations. To rectify these problems, we modify update procedure for the best particle in the swarm and propose a simple and random moving strategy. We perform a Reduced Variable Neighborhood Search (RVNS) based local search …