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Full-Text Articles in Physical Sciences and Mathematics
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, …
Design Optimization Of Distribution Transformers With Nature-Inspired Metaheuristics: A Comparative Analysis, Levent Alhan, Nejat Yumuşak
Design Optimization Of Distribution Transformers With Nature-Inspired Metaheuristics: A Comparative Analysis, Levent Alhan, Nejat Yumuşak
Turkish Journal of Electrical Engineering and Computer Sciences
Many economies in the world have adopted energy-efficiency requirements or incentive programs mandating or promoting the use of energy-efficient transformers. On the other hand, increases in transformer efficiency are subject to increases in transformer weight and size, sometimes as much as 50% or more. The transformer manufacturing industry is therefore faced with the challenge to develop truly optimum designs. Transformer design optimization (TDO) is a mixed-integer nonlinear programming problem having a complex and discontinuous objective function and constraints, with the objective of detailed calculation of the characteristics of a transformer based on national and/or international standards and transformer user requirements, …
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 …
Square Root Central Difference-Based Fastslam Approach Improved By Differential Evolution, Haydar Ankişhan, Fi̇kret Ari, Emre Öner Tartan, Ahmet Güngör Pakfi̇li̇z
Square Root Central Difference-Based Fastslam Approach Improved By Differential Evolution, Haydar Ankişhan, Fi̇kret Ari, Emre Öner Tartan, Ahmet Güngör Pakfi̇li̇z
Turkish Journal of Electrical Engineering and Computer Sciences
This study presents a new approach to improve the performance of FastSLAM. The aim of the study is to obtain a more robust algorithm for FastSLAM applications by using a Kalman filter that uses Stirling's polynomial interpolation formula. In this paper, some new improvements have been proposed; the first approach is the square root central difference Kalman filter-based FastSLAM, called SRCD-FastSLAM. In this method, autonomous vehicle (or robot) position, landmarks' position estimations, and importance weight calculations of the particle filter are provided by the SRCD-Kalman filter. The second approach is an improved version of the SRCD-FastSLAM in which particles are …
Short-Term Economic Emission Power Scheduling Of Hydrothermal Systems Using Improved Chaotic Hybrid Differential Evolution, Tahir Nadeem Malik, Salman Zafar, Saaqib Haroon
Short-Term Economic Emission Power Scheduling Of Hydrothermal Systems Using Improved Chaotic Hybrid Differential Evolution, Tahir Nadeem Malik, Salman Zafar, Saaqib Haroon
Turkish Journal of Electrical Engineering and Computer Sciences
utilities to retain their generations within maximum allowable emission levels. Therefore, in present-day power system operations, the minimization of emission pollutants along with the total fuel cost has become an important aspect in short-term generation scheduling of hydrothermal power systems. This paper presents an improved hybrid approach based on the application of chaos theory in a differential evolution (DE) algorithm for the solution of this biobjective constrained optimization problem. In this proposed methodology, self-adjusted parameter setting in DE is obtained by using chaotic sequences. Secondly, a chaotic hybridized local search mechanism is embedded in DE to avoid it from trapping …
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 …
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 …
Opf-Based Reactive Power Planning And Voltage Stability Limit Improvement Under Single Line Outage Contingency Condition Through Evolutionary Algorithms, Sakthivel Padaiyatchi, Mary Daniel
Opf-Based Reactive Power Planning And Voltage Stability Limit Improvement Under Single Line Outage Contingency Condition Through Evolutionary Algorithms, Sakthivel Padaiyatchi, Mary Daniel
Turkish Journal of Electrical Engineering and Computer Sciences
Reactive power planning is vital for maintaining the voltage stability of power systems and evolutionary algorithms are highly useful for achieving this task. This paper compares the effectiveness of the differential evolution (DE) and evolutionary programming (EP) algorithms in optimizing the reactive power planning of power systems under line outage contingency conditions. DE is efficient in exploration through the search space of the problem, while EP is simple and easy to implement. The low cost but fast response thyristor-controlled series capacitor (TCSC) flexible alternating current transmission system (FACTS) device is incorporated to control the power flows. The optimal settings of …
Multiobjective Differential Evolution-Based Performance Optimization For Switched Reluctance Motor Drives, Hedi Yahia, Noureddine Liouane, Rachid Dhifaoui
Multiobjective Differential Evolution-Based Performance Optimization For Switched Reluctance Motor Drives, Hedi Yahia, Noureddine Liouane, Rachid Dhifaoui
Turkish Journal of Electrical Engineering and Computer Sciences
The simple structure, low manufacturing cost, rugged behavior, high torque per unit volume, and wide torque-speed range make a switched reluctance motor (SRM) very attractive for industrial applications. However, these advantages are overshadowed by its inherent high torque ripple, acoustic noise, and difficulty to control. The controlled parameters in SRM drives can be selected as the turn-on angle, the turn-off angle, and the current reference. This paper investigates the problem of optimal control parameters considering the maximum average torque, minimum copper losses, and minimum torque ripple as the main objectives in SRM drives. The use of evolutionary algorithms (EAs) to …
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 …
Evolutionary Algorithms For The Unit Commitment Problem, A. Şi̇ma Uyar, Belgi̇n Türkay
Evolutionary Algorithms For The Unit Commitment Problem, A. Şi̇ma Uyar, Belgi̇n Türkay
Turkish Journal of Electrical Engineering and Computer Sciences
This paper compares three evolutionary computation techniques, namely Steady-State Genetic Algorithms, Evolutionary Strategies and Differential Evolution for the Unit Commitment Problem. The comparison is based on a set of experiments conducted on benchmark datasets as well as on real-world data obtained from the Turkish Interconnected Power System. The results of two state-of-the-art evolutionary approaches, namely a Generational Genetic Algorithm and a Memetic Algorithm for the same benchmark datasets are also included in the paper for comparison. The tests show that Differential Evolution is the best performer among all approaches on the test data used in the paper. The performances of …