Open Access. Powered by Scholars. Published by Universities.®
- Discipline
-
- Computer Sciences (107)
- Physical Sciences and Mathematics (107)
- Electrical and Computer Engineering (60)
- Artificial Intelligence and Robotics (48)
- Numerical Analysis and Scientific Computing (48)
-
- Operations Research, Systems Engineering and Industrial Engineering (48)
- Systems Science (48)
- Other Computer Engineering (3)
- Robotics (3)
- Biomedical Engineering and Bioengineering (2)
- Mechanical Engineering (2)
- Biochemistry, Biophysics, and Structural Biology (1)
- Bioelectrical and Neuroengineering (1)
- Biomedical (1)
- Chemical Engineering (1)
- Chemicals and Drugs (1)
- Civil and Environmental Engineering (1)
- Computational Engineering (1)
- Computer and Systems Architecture (1)
- Controls and Control Theory (1)
- Digital Circuits (1)
- Diseases (1)
- Electrical and Electronics (1)
- Female Urogenital Diseases and Pregnancy Complications (1)
- Hardware Systems (1)
- Library and Information Science (1)
- Life Sciences (1)
- Materials Science and Engineering (1)
- Institution
- Publication Year
- Publication
-
- Turkish Journal of Electrical Engineering and Computer Sciences (58)
- Journal of System Simulation (48)
- Computer Science Faculty Publications (2)
- Al-Esraa University College Journal for Engineering Sciences (1)
- Boise State University Theses and Dissertations (1)
-
- Computer Science and Engineering Research (1)
- Conference papers (1)
- Dissertations, Master's Theses and Master's Reports (1)
- Electronic Theses and Dissertations (1)
- Faculty and Staff Scholarship (1)
- Iraqi Journal for Computer Science and Mathematics (1)
- Journal of Soft Computing and Computer Applications (1)
- LSU New Orleans Theses and Dissertations (1)
- Library Philosophy and Practice (e-journal) (1)
- Publication Type
Articles 61 - 90 of 119
Full-Text Articles in Computer Engineering
Current Sensor Fault Diagnosis For Induction Motor In Vector Control System, Sun Kai, Baina He, Sarah Odofin, Gu Yu
Current Sensor Fault Diagnosis For Induction Motor In Vector Control System, Sun Kai, Baina He, Sarah Odofin, Gu Yu
Journal of System Simulation
Abstract: A current sensor fault diagnosis method of induction motor in vector control system is proposed. A state-space form including sensor faults and environmental disturbances/noises of induction machine is described. An augmented observer is designed to simultaneously estimate system states, and current sensor faults. To attenuate the effects from the environmental disturbances/noises, a genetic algorithm is employed to design observer gain by minimizing the estimation error against environmental disturbances and noises. A simulation model based on Matlab and real-data of the induction motor collected by experiment is utilized to validate the proposed methods, which show the efficiency of the proposed …
Modeling And Simulation Of Pid Networked Control Systems Based On Neural Network, Zhanzhi Qiu, Shifeng Li
Modeling And Simulation Of Pid Networked Control Systems Based On Neural Network, Zhanzhi Qiu, Shifeng Li
Journal of System Simulation
Abstract: According to the problems of the delay compensation and PID parameters tuning of networked control systems, a class of rapid PID networked control systems based on improved BP network was proposed. Considering the problems of obtaining hidden layer nodes number and local optimum of the BP network delay prediction model, a calculation method was proposed to obtain hidden layer nodes number, and an improved genetic algorithm was proposed to train the BP network. Considering the problems of integral saturation, parameters tuning and model mismatch of the PID network control systems, a PID parameter adjuster was designed based on …
Improved Bp Neural Network Of Heat Load Forecasting Based On Temperature And Date Type, Li Qi, Zhao Feng
Improved Bp Neural Network Of Heat Load Forecasting Based On Temperature And Date Type, Li Qi, Zhao Feng
Journal of System Simulation
Abstract: The heat load forecasting provides data support for urban district heating systems, which is the basis of need-based heating. The change of heat load is greatly influenced by various exterior factors, especially the outdoor temperature. To meet demand of heating system, save energy and balance the comfort of human body, a kind of improved BP neural network method is proposed by temperature and date type. The temperature and date type are quantified and the heat load forecasting model is established by using BP neural network. To guarantee prediction accuracy, the genetic algorithm is used to optimize the weights and …
Simulation Of Wind Power Prediction Based On Improved Elm, Wang Hao, Wang Yan, Zhicheng Ji
Simulation Of Wind Power Prediction Based On Improved Elm, Wang Hao, Wang Yan, Zhicheng Ji
Journal of System Simulation
Abstract: To predict the range of ultra-short-term wind power fluctuation effectively, a combined forecasting model based on fuzzy information granulation (FIG) and genetic algorithm optimization extreme learning machine (GA-ELM) is proposed. The parameters of wind power are granulated by fuzzy information, and the corresponding valid information including the maximal value, the minimum value, and the general average value in time series window is further extracted. By integrating the effective components of each parameter as training samples, the GA-ELM-based prediction model is established. The range of wind power fluctuation in next time series is forecasted through using the optimized model. The …
Simulation Optimization On Multi-Ports Slot Plan Problem Considering Dispatching Sequence Of Containers In Yard, Zhang Yu, Huimin Cheng, Xu Jin, Tian Wei, Junfeng Sun
Simulation Optimization On Multi-Ports Slot Plan Problem Considering Dispatching Sequence Of Containers In Yard, Zhang Yu, Huimin Cheng, Xu Jin, Tian Wei, Junfeng Sun
Journal of System Simulation
Abstract: The multi-ports slot plan problem considering dispatching sequence of containers in yard is solved by an integer linear programming model, which minimizes heeling moment. The influences of different dispatching rules on solving the problem are simulated and analyzed through the programming model. Accordingly, a simulation optimization model based on genetic algorithm is constructed in order to enhance the computational efficiency. The simulation optimization model simulates the process of dispatching containers and loading vessel. The feasible solution is constructed through rules sets and inputted into the optimization model. An efficient encoding and decoding solutions are developed in genetic algorithm, …
Fuzzy Sliding Backstepping Mode Control For Flight Simulator Servo Based On Friction And Disturbance Compensation, Huibo Liu, Shanglei Liu
Fuzzy Sliding Backstepping Mode Control For Flight Simulator Servo Based On Friction And Disturbance Compensation, Huibo Liu, Shanglei Liu
Journal of System Simulation
Abstract: Considering friction, modeling errors and other uncertainties of flight simulator servo system, a compensation strategy which combines model-based friction compensation with nonlinear disturbance observer compensation was proposed. First, the friction is modeled , whose parameters are identified by using genetic algorithm, and using the identified model to compensate. Second, using a nonlinear disturbance observer to estimate the modeling errors, friction less-compensation or over-compensation and other uncertainties, and using this observed value to compensate. The system adopted sliding backstepping controller to ensure the stabilization of the system. Finally, the fuzzy algorithm is adopted to adjust the switching gain of sliding …
Generation Rescheduling Using Multiobjective Bilevel Optimization, Kiran Babu Vakkapatla, Srinivasa Varma Pinni
Generation Rescheduling Using Multiobjective Bilevel Optimization, Kiran Babu Vakkapatla, Srinivasa Varma Pinni
Turkish Journal of Electrical Engineering and Computer Sciences
This paper presents a new multiobjective optimization method that can be used for generation rescheduling in power systems. Generation rescheduling in restructured power systems is performed by the system operator for different operations like congestion management, day-ahead scheduling, and preventive maintenance. The nonlinear nature of the equations involved and the constraints on decision variables pose a challenge to find the global optimum. In order to find the global optimum using a genetic algorithm, a bilevel optimization method is proposed. In the proposed multiobjective optimization method, the objectives are classified as primary and secondary based on their relative importance. The best …
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. …
Optimized Bilevel Classifier For Brain Tumor Type And Grade Discrimination Using Evolutionary Fuzzy Computing, Kavitha Srinivasan, Mohanavalli Subramaniam, Bharathi Bhagavathsingh
Optimized Bilevel Classifier For Brain Tumor Type And Grade Discrimination Using Evolutionary Fuzzy Computing, Kavitha Srinivasan, Mohanavalli Subramaniam, Bharathi Bhagavathsingh
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper, an optimized bilevel brain tumor diagnostic system for identifying the tumor type at the first level and grade of the identified tumor at the second level is proposed using genetic algorithm, decision tree, and fuzzy rule-based approach. The dataset is composed of axial MRI of brain tumor types and grades. From the images, various features such as first and second order statistical and textural features are extracted (26 features). In the first level, tumor type classification was done using decision tree constructed with all features. Further evolutionary computing using genetic algorithms (GA) was applied to select the …
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 …
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 …
Gacnn Sleeptunenet: A Genetic Algorithm Designing The Convolutional Neural Network Architecture For Optimal Classification Of Sleep Stages From A Single Eeg Channel, Shahnawaz Qureshi, Seppo Karilla, Sirirut Vanichayobon
Gacnn Sleeptunenet: A Genetic Algorithm Designing The Convolutional Neural Network Architecture For Optimal Classification Of Sleep Stages From A Single Eeg Channel, Shahnawaz Qureshi, Seppo Karilla, Sirirut Vanichayobon
Turkish Journal of Electrical Engineering and Computer Sciences
This study presents a method for designing--by a genetic algorithm, without manual intervention--the feature learning architecture for classification of sleep stages from a single EEG channel, when using a convolutional neural network called GACNN SleepTuneNet. Two EEG electrode positions were selected, namely FP2-F4 and FPz-Cz, from two available datasets. Twenty-five generations were involved in diagnosis without hand-crafted features, to learn the architecture for classification of sleep stages based on AASM standard. Based on the results, our model not only achieved the highest classification accuracy, but it also distinguished the sleep stages based on either of the two EEG electrode signals, …
Automatic Prostate Segmentation Using Multiobjective Active Appearance Model In Mr Images, Ahad Salimi, Mohammad Ali Pourmina, Mohamma-Shahram Moien
Automatic Prostate Segmentation Using Multiobjective Active Appearance Model In Mr Images, Ahad Salimi, Mohammad Ali Pourmina, Mohamma-Shahram Moien
Turkish Journal of Electrical Engineering and Computer Sciences
Prostate cancer is the second largest cause of mortality among men. Prostate segmentation, i.e. the precise determination of the prostate region in magnetic resonance imaging (MRI), is generally used for prostate volume measurement, which can be used as a potential prostate cancer indicator. This paper presents a new fully automatic statistical model called the multiobjective active appearance model (MOAAM) for prostate segmentation in MR images. First, in the training stage, the appearance model, including the shape and texture model, is developed by applying principal component analysis to the training images, already outlined by a physician. Then noise and roughness are …
Modeling And Simulation Methodologies For Spinal Cord Stimulation., Saliya Kumara Kirigeeganage
Modeling And Simulation Methodologies For Spinal Cord Stimulation., Saliya Kumara Kirigeeganage
Electronic Theses and Dissertations
The use of neural prostheses to improve health of paraplegics has been a prime interest of neuroscientists over the last few decades. Scientists have performed experiments with spinal cord stimulation (SCS) to enable voluntary motor function of paralyzed patients. However, the experimentation on the human spinal cord is not a trivial task. Therefore, modeling and simulation techniques play a significant role in understanding the underlying concepts and mechanics of the spinal cord stimulation. In this work, simulation and modeling techniques related to spinal cord stimulation were investigated. The initial work was intended to visualize the electric field distribution patterns in …
Why We Do Not Evolve Software? Analysis Of Evolutionary Algorithms, Roman V. Yampolskiy
Why We Do Not Evolve Software? Analysis Of Evolutionary Algorithms, Roman V. Yampolskiy
Faculty and Staff Scholarship
In this article, we review the state-of-the-art results in evolutionary computation and observe that we do not evolve nontrivial software from scratch and with no human intervention. A number of possible explanations are considered, but we conclude that computational complexity of the problem prevents it from being solved as currently attempted. A detailed analysis of necessary and available computational resources is provided to support our findings.
Modeling And Simulation Of Networked Control Systems Based On Improved Bp Network, Shifeng Li, Zhanzhi Qiu, Liping Fan, Lina Zhao
Modeling And Simulation Of Networked Control Systems Based On Improved Bp Network, Shifeng Li, Zhanzhi Qiu, Liping Fan, Lina Zhao
Journal of System Simulation
Abstract: In the circumstance where both the delay model and the controlled object model were unknown in networked control systems, a class of networked predictive control systems based on improved BP network were studied. For the problem of obtaining the hidden layer nodes number of BP network, a rapid calculation method was proposed. For the problem of avoiding local optimum of BP network, a hybrid learning method was proposed. A off-line BP network model was proposed for coping with the problem of the delay prediction based on the above algorithms. For the problem of the linear …
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 …
Multiobjective Aerodynamic Optimization Of A Microscale Ducted Wind Turbineusing A Genetic Algorithm, Emre Alpman
Multiobjective Aerodynamic Optimization Of A Microscale Ducted Wind Turbineusing A Genetic Algorithm, Emre Alpman
Turkish Journal of Electrical Engineering and Computer Sciences
A two-objective aerodynamic optimization of a microscale ducted wind turbine was performed using a genetic algorithm. Two different fitness function pairs were considered for this purpose. In the first alternative the algorithm maximized the power produced while minimizing the drag force at a given wind speed and tip speed ratio. In the second alternative, however, the annual energy production was maximized while minimizing the maximum drag force developed between the cut-in and cut-off wind speeds. Computational uid dynamics solutions performed for selected best designs showed that optimizations performed using the second alternative yielded better turbines, which could produce more power …
Symbolic Interpretation Of Artificial Neural Networks Using Genetic Algorithms, Dounia Yedjour, Abdelkader Benyettou, Hayat Yedjour
Symbolic Interpretation Of Artificial Neural Networks Using Genetic Algorithms, Dounia Yedjour, Abdelkader Benyettou, Hayat Yedjour
Turkish Journal of Electrical Engineering and Computer Sciences
The knowledge acquired during the learning of artificial neural networks (ANNs) is coded as values in synaptic weights, which makes their interpretations difficult, hence the name of the black box. The aim of this work is to provide a comprehensible interpretation of the ANN's decisions by extracting symbolic rules. We improve the performance of our extraction algorithm by combining the ANN with a genetic algorithm. Misleading rules whose support and confidence values are less than fixed thresholds are removed and, as a result, the comprehensibility is improved. The extracted rules are evaluated and compared with other works. The results show …
A Modified Genetic Algorithm For A Special Case Of The Generalized Assignment Problem, Murat Dörterler, Ömer Faruk Bay, Mehmet Ali̇ Akcayol
A Modified Genetic Algorithm For A Special Case Of The Generalized Assignment Problem, Murat Dörterler, Ömer Faruk Bay, Mehmet Ali̇ Akcayol
Turkish Journal of Electrical Engineering and Computer Sciences
Many central examinations are performed nationwide in Turkey. These examinations are held simultaneously throughout Turkey. Examinees attempt to arrive at the examination centers at the same time and they encounter problems such as traffic congestion, especially in metropolises. The state of mind that this situation puts them into negatively affects the achievement and future goals of the test takers. Our solution to minimize the negative effects of this issue is to assign the test takers to closest examination centers taking into account the capacities of examination halls nearby. This solution is a special case of the generalized assignment problem (GAP). …
Assessment Of Disordered Voices Based On An Optimized Glottal Source Model, Mounir Boudjerda, Abdellah Kacha
Assessment Of Disordered Voices Based On An Optimized Glottal Source Model, Mounir Boudjerda, Abdellah Kacha
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper, a method for the assessment of disordered voices is proposed. A feature named mean opening quotient (MOQ) obtained from the glottal source estimation is used as an acoustic cue to summarize the degree of severity of the voice disorder. The analysis method uses the empirical mode decomposition algorithm to estimate the glottal source excitation signal from the speech signal. The logarithm of the magnitude spectrum of the speech signal is decomposed into oscillatory modes, called intrinsic mode functions, that are clustered into two classes, the spectral envelope and the harmonic component. The exploitation of the phase information …
Developing A Model And Software For Energy Efficiency Optimization In The Building Design Process: A Case Study In Turkey, Özgür Bayata, İzzetti̇n Temi̇z
Developing A Model And Software For Energy Efficiency Optimization In The Building Design Process: A Case Study In Turkey, Özgür Bayata, İzzetti̇n Temi̇z
Turkish Journal of Electrical Engineering and Computer Sciences
Buildings are responsible for 40% of the primary energy consumption in the world. Recent studies have revealed that the energy efficiency and environmental impact of buildings are two very important criteria to consider during the process of building design for the future of our world. By considering the initial investment cost and its importance for investors, a problem with three objective functions has emerged with 16 building energy systems and 24 construction material alternatives. The aim of this work is to develop a methodology and software to solve multiobjective building optimization problems. Thus, two different software tools have been developed …
An Improved Omthd Technique For An N-Level Cascaded Multilevel Inverter With Adjustable Dc Sources, Hamidreza Toodeji
An Improved Omthd Technique For An N-Level Cascaded Multilevel Inverter With Adjustable Dc Sources, Hamidreza Toodeji
Turkish Journal of Electrical Engineering and Computer Sciences
Optimal minimization of total harmonic distortion (OMTHD) and selective harmonic elimination (SHE) switching techniques are usually employed to reduce generated harmonics of multilevel inverters. In the former technique, the THD of waveform is reduced without elimination of any harmonic order and the latter, in contrast, eliminates selected harmonic orders. In this paper, the harmonic elimination ability of the SHE technique is added to OMTHD and an improved OMTHD technique is proposed for an n-level cascaded multilevel inverter with adjustable DC sources. The main novelty of this switching technique is elimination of some harmonic orders, beside THD minimization. Moreover, optimal DC …
Energy Efficient Multiconstrained Optimization Using Hybrid Aco And Ga In Manet Routing, Nivetha Senthil Kumaran, Asokan Ramasamy
Energy Efficient Multiconstrained Optimization Using Hybrid Aco And Ga In Manet Routing, Nivetha Senthil Kumaran, Asokan Ramasamy
Turkish Journal of Electrical Engineering and Computer Sciences
Nodes in mobile ad hoc networks (MANET) suffer from limited battery power and bandwidth. Particularly for real time multimedia communications through MANET, metrics like residual node energy, bandwidth, and end-to-end delay have major impacts. In MANET, designing a dynamic routing algorithm to satisfy quality of service (QoS) requirements is a challenging task. Additionally, multiconstrained QoS routing aims to optimize multiple QoS metrics while providing required network resources and is an admittedly complex problem. It has been proved to be NP-complete when a combination of additive, concave, and multiplicative metrics are considered. Hence, this problem can be solved using metaheuristic methods …
A Ring Crossover Genetic Algorithm For The Unit Commitment Problem, Syed Basit Ali Bukhari, Aftab Ahmad, Syed Auon Raza, Muhammad Noman Siddique
A Ring Crossover Genetic Algorithm For The Unit Commitment Problem, Syed Basit Ali Bukhari, Aftab Ahmad, Syed Auon Raza, Muhammad Noman Siddique
Turkish Journal of Electrical Engineering and Computer Sciences
The unit commitment problem (UCP) is a nonlinear, mixed-integer, constraint optimization problem and is considered a complex problem in electrical power systems. It is the combination of two interlinked subproblems, namely the generator scheduling problem and the generation allocation problem. In large systems, the UCP turns out to be increasingly complicated due to the large number of possible ON and OFF combinations of units in the power system over a scheduling time horizon. Due to the insufficiency of conventional approaches in handling large systems, numerous metaheuristic techniques are being developed for solving this problem. The genetic algorithm (GA) is one …
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, …
A Problem Approximation Surrogate Model (Pasm) For Fitness Approximation In Optimizing The Quantization Table For The Jpeg Baseline Algorithm, Vinoth Kumar Balasubramanian, Karpagam Manavalan
A Problem Approximation Surrogate Model (Pasm) For Fitness Approximation In Optimizing The Quantization Table For The Jpeg Baseline Algorithm, Vinoth Kumar Balasubramanian, Karpagam Manavalan
Turkish Journal of Electrical Engineering and Computer Sciences
The quantization table in the baseline Joint Photographic Experts Group (JPEG) algorithm plays an important role in compression/quality trade-off. Hence the detection of the optimal quantization table is viewed as an optimization problem. The genetic algorithm (GA) is an attractive optimization tool by many researchers for this application due to its ability in dealing with complex problems. In spite of its advantages, the GA requires more computation time to achieve an optimal solution if it has an expensive fitness evaluation. This paper proposes a problem approximation surrogate model (PASM) for fitness approximation to assist the GA in optimizing the quantization …
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 …
Design And Implementation Of A Genetic Algorithm Ip Core On An Fpga For Path Planning Of Mobile Robots, Adem Tuncer, Mehmet Yildirim
Design And Implementation Of A Genetic Algorithm Ip Core On An Fpga For Path Planning Of Mobile Robots, Adem Tuncer, Mehmet Yildirim
Turkish Journal of Electrical Engineering and Computer Sciences
This paper presents a hardware realization of a genetic algorithm (GA) for the path planning problem of mobile robots on a field programmable gate array (FPGA). A customized GA intellectual property (IP) core was designed and implemented on an FPGA. A Xilinx xupv5-lx110t FPGA device was used as the hardware platform. The proposed GA IP core was applied to a Pioneer 3-DX mobile robot to confirm its path planning performance. For localization tasks, a camera mounted on the ceiling of the laboratory was utilized to receive images and allow the robot to determine its own location and the obstacles in …
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. …