Engineering Commons^™

Task Offloading And Resource Allocation Based On Dl-Ga In Mobile Edge Computing, Hang Gu, Minjuan Zhang, Wenzao Li, Yuwen Pan

Turkish Journal of Electrical Engineering and Computer Sciences

With the rapid development of 5G and the Internet of Things (IoT), the traditional cloud computing architecture struggle to support the booming computation-intensive and latency-sensitive applications. Mobile edge computing (MEC) has emerged as a solution which enables abundant IoT tasks to be offloaded to edge services. However, task offloading and resource allocation remain challenges in MEC framework. In this paper, we add the total number of offloaded tasks to the optimization objective and apply algorithm called Deep Learning Trained by Genetic Algorithm (DL-GA) to maximize the value function, which is defined as a weighted sum of energy consumption, latency, and …

Metaheuristic Optimization Techniques Used In Controlling Of An Active Magnetic Bearing System For High-Speed Machining Application, Suraj Suraj, Pabitra Kumar Biswas Pabitra Kumar Biswas, Sukanta Debnath, Anumoy Ghosh, Thanikanti Sudhakar Babu, Hossam Zawbaa, Salah Kemal

Articles

Smart control tactics, wider stability region, rapid reaction time, and high-speed performance are essential requirements for any controller to provide a smooth, vibrationless, and efficient performance of an in-house fabricated active magnetic bearing (AMB) system. In this manuscript, three pre-eminent population-based metaheuristic optimization techniques: Genetic algorithm (GA), Particle swarm optimization (PSO), and Cuckoo search algorithm (CSA) are implemented one by one, to calculate optimized gain parameters of PID controller for the proposed closed-loop active magnetic bearing (AMB) system. Performance indices or, objective functions on which these optimization techniques are executed are integral absolute error (IAE), integral square error (ISE), integral …

System Level Pdn Impedance Optimization Utilizing The Zeros Of The Decoupling Capacitors, Yifan Ding, Shuang Liang, Francesco De Paulis, Matteo Cocchini, Samuel Connor, Matthew Doyle, Albert E. Ruehli, Chulsoon Hwang, James L. Drewniak

Electrical and Computer Engineering Faculty Research & Creative Works

System-Level Power Distribution Network (PDN) Impedance Optimization Utilizing the Zeros of the Decoupling Capacitors (Decaps) is Discussed in This Paper. an Example of a Practical PDN Application is Proposed to Validate the Poles and Zeros Algorithm (P&Z) Presented. the System-Level PDN is with the Printed Circuit Board (PCB), Package (PKG), and Chip, as Well as the Low-Frequency Decaps on the PCB and the On-PKG Decoupling Capacitors. the PDN Optimization Results Are Compared with Those from the Genetic Algorithm (GA) to Show the Reasonableness and Validity of the P&Z Algorithm.

Optimization Of High-Speed Channel For Signal Integrity With Deep Genetic Algorithm, Huan Huan Zhang, Zhao Sheng Xue, Xin Yi Liu, Ping Li, Lijun Jiang, Guang Ming Shi

Electrical and Computer Engineering Faculty Research & Creative Works

A deep genetic algorithm (GA) is proposed to optimize the high-speed channel for signal integrity. In the traditional genetic algorithm-based high-speed channel optimization method, the eye height and eye width of the eye diagram are obtained by eye diagram simulation based on the full-wave algorithm, which is computationally expensive. In this letter, a deep neural network (DNN) is trained to predict the eye diagram information corresponding to a set of given design parameters of the high-speed channel. This DNN is embedded into the genetic algorithm to carry out the evaluation operation, which can greatly accelerate the evaluation process. A high-speed …

Optimizing Speed Profiles For Sustainable Train Operation With Wayside Energy Storage Systems, Leon A. Allen

Dissertations

Large hauling capability and low rolling resistance has put rail transit at the forefront of mass transportation mode sustainability in terms of congestion mitigation and energy conservation. As such, rail vehicles are one of the least energy-intensive modes of transportation and least environmentally polluting. Despite, these positives, improper driving habits and wastage of the braking energy through dissipation in braking resistors result in unnecessary consumption, extra costs to the operator and increased atmospheric greenhouse gas emissions.

This study presents an intelligent method for the optimization of the number and locations of wayside energy storage system (WESS) units that maximize the …

A Methodical Approach For Pcb Pdn Decoupling Minimizing Overdesign With Genetic Algorithm Optimization, F. De Paulis, Y. Ding, M. Cocchini, Chulsoon Hwang, S. Connor, M. Doyle, S. Scearce, W. D. Becker, Albert E. Ruehli, James L. Drewniak

Electrical and Computer Engineering Faculty Research & Creative Works

An optimization routine is applied for the decoupling capacitor placement on Power Distribution Networks to identify the limit beyond which the placement of additional decaps is no longer effective, thus leading to wasting layout area and components, and to a cost increase. A specific test example from a real design is used together with the required target impedance and frequency band of interest for the PDN design. The effectiveness of the decap placement while selecting different layers of the stack-up, and while moving the upper limit of the PDN design band is analyzed. Such analysis leads to helpful insights based …

Selective Harmonic Mitigation Based Two-Scale Frequency Control Of Cascaded Modified Packed U-Cell Inverters, Hasan Iqbal, Mohd Tariq, Mohammad Sarfraz, Arif I. Sarwat, Waleed Alhosaini, Obaid Aldosari, Asma Aziz

Research outputs 2022 to 2026

A new Modified Packed U-Cell (MPUC) converter architecture with cascading is proposed in this paper. To provide an output voltage of 25 levels, the proposed cascaded MPUC needs only twelve power switches and four power sources. The converter comprises two cascaded MPUCs with DC supply in a ratio of 5 : 1. One converter is operating at low frequency (LF) and the other at high frequency (HF) that leads to lower power losses and higher levels. Besides, a variable frequency method is anticipated to produce a 25-level output voltage which has low harmonic content (THD) with the help of Selective …

Optimal Sizing And Energy Scheduling Of Grid-Supplemented Solar Pv Systems With Battery Storage: Sensitivity Of Reliability And Financial Constraints, Aakash Hassan, Yasir M. Al-Abdeli, Martin Masek, Octavian Bass

Research outputs 2022 to 2026

Establishing reliable, clean, and inexpensive solar PV systems is a complex interplay between the level of reliability (LPSP), financial constraints, and CO2 emissions. This paper investigates the impact of these factors on stand-alone (SA) and grid-supplemented (GS) solar PV systems over multiple seasons. The research uses established hardware models, detailed power management strategies as well as realistic Australian grid tariffs and Genetic Algorithms to find the minimum Cost of Energy (COE) subject to LPSP and financial constraints. The developed power management strategies are also tested experimentally on a real solar PV system. The results indicate that the grid-supplemented system yields …

A New Hybrid Genetic Algorithm For Protein Structure Prediction On The 2dtriangular Lattice, Bouroubi Sadek, Nabil Boumedine

Turkish Journal of Electrical Engineering and Computer Sciences

The flawless functioning of the protein is essentially related to its three-dimensional structure. Therefore,predicting protein structure from its amino acid sequence is a fundamental problem that draws researchers' attentionin many areas. The protein structure prediction problem (PSP) can be formulated as a combinatorial optimization problem based on simplified lattice models such as the hydrophobic-polar model. In this paper, we propose a new hybridalgorithm that combines three different known heuristic algorithms: the genetic algorithm, the tabu search strategy,and the local search algorithm to solve the PSP problem. Regarding the evaluation of the proposed approach, wepresent an experimental study, where we consider …

Analysis Of Shielding Effectiveness By Optimizing Aperture Dimensions Of Arectangular Enclosure With Genetic Algorithm, Sunay Güler, Si̇bel Yeni̇kaya

Turkish Journal of Electrical Engineering and Computer Sciences

Electromagnetic compatibility (EMC) has now become a substantial challenge more than any other time sincethe number of electric vehicles (EV) increased rapidly. The electric driving system in an EV consists of power electroniccomponents supplied by high voltage battery source. They are both source and victim of potential electromagneticinterference (EMI) since fast switching process occurs inside them. Electromagnetic shielding provides a significantprotection against EMI for any electrical and electronic components inside the vehicle. In this paper, analysis of shieldingeffectiveness (SE) by optimizing aperture dimensions of a rectangular enclosure is investigated. Realistic dimensions of theshielding enclosure of an inverter component are employed. …

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 …

Information Retrieval-Based Bug Localization Approach With Adaptive Attributeweighting, Mustafa Erşahi̇n, Semi̇h Utku, Deni̇z Kilinç, Buket Erşahi̇n

Turkish Journal of Electrical Engineering and Computer Sciences

Software quality assurance is one of the crucial factors for the success of software projects. Bug fixing has an essential role in software quality assurance, and bug localization (BL) is the first step of this process. BL is difficult and time-consuming since the developers should understand the flow, coding structure, and the logic of the program. Information retrieval-based bug localization (IRBL) uses the information of bug reports and source code to locate the section of code in which the bug occurs. It is difficult to apply other tools because of the diversity of software development languages, design patterns, and development …

Gene Expression Data Classification Using Genetic Algorithm-Basedfeature Selection, Öznur Si̇nem Sönmez, Mustafa Dağteki̇n, Tolga Ensari̇

Turkish Journal of Electrical Engineering and Computer Sciences

In this study, hybrid methods are proposed for feature selection and classification of gene expression datasets. In the proposed genetic algorithm/support vector machine (GA-SVM) and genetic algorithm/k nearest neighbor (GA-KNN) hybrid methods, genetic algorithm is improved using Pearson's correlation coefficient, Relief-F, or mutual information. Crossover and selection operations of the genetic algorithm are specialized. Eight different gene expression datasets are used for classification process. The classification performances of the proposed methods are compared with the traditional GA-KNN and GA-SVM wrapper methods and other studies in the literature. Classification results demonstrate that higher accuracy rates are obtained with the proposed methods …

Heuristic Approaches For Near-Optimal Placement Of Gps-Based Multi-Static Radar Receivers In American Coastal Waters, Brandon J. Hufstetler

Theses and Dissertations

Narcotics smuggling across the Caribbean Sea is a growing concern for the United States Coast Guard. One vector for this illicit trafficking is via small aircraft. This thesis proposes a multi-static radar architecture using the Global Positioning System (GPS) constellation as a transmission source to detect these aircraft as they transit a detection fence. The system developed in this thesis relies on the forward-scatter phenomenon in which a radar shadow is cast by a target as it crosses in front of a transmitter, creating a measurable difference in the signal amplitude at the receiver. This thesis first develops a mathematical …

A New Biometric Identity Recognition System Based On A Combination Of Superior Features In Finger Knuckle Print Images, Hadis Heidari, Abdolah Chalechale

Turkish Journal of Electrical Engineering and Computer Sciences

Biometric methods are among the safest and most secure solutions for identity recognition and verification. One of the biometric features with sufficient uniqueness for identity recognition is the finger knuckle print (FKP). This paper presents a new method of identity recognition and verification based on FKP features, where feature extraction is combined with an entropy-based pattern histogram and a set of statistical texture features. The genetic algorithm (GA) is then used to find the superior features among those extracted. After extracting superior features, a support vector machine-based feedback scheme is used to improve the performance of the biometric system. Two …

A Fast Text Similarity Measure For Large Document Collections Using Multireference Cosine And Genetic Algorithm, Hamid Mohammadi, Seyed Hossein Khasteh

Turkish Journal of Electrical Engineering and Computer Sciences

One of the critical factors that make a search engine fast and accurate is a concise and duplicate free index. In order to remove duplicate and near-duplicate (DND) documents from the index, a search engine needs a swift and reliable DND text document detection system. Traditional approaches to this problem, such as brute force comparisons or simple hash-based algorithms, are not suitable as they are not scalable and are not capable of detecting near-duplicate documents effectively. In this paper, a new signature-based approach to text similarity detection is introduced, which is fast, scalable, and reliable and needs less storage space. …

Chemical Disease Relation Extraction Task Using Genetic Algorithm With Two Novelvoting Methods For Classifier Subset Selection, Stanley Chika Onye, Nazi̇fe Di̇mi̇li̇ler, Ari̇f Akkeleş

Turkish Journal of Electrical Engineering and Computer Sciences

Biomedical relation extraction is an important preliminary step for knowledge discovery in the biomedical domain. This paper proposes a multiple classifier system (MCS) for the extraction of chemical-induced disease relations. A genetic algorithm (GA) is employed to select classifier ensembles from a pool of base classifiers. Moreover, the voting method used for combining the members of each of the ensembles is also selected during evolution in the GA framework. The performances of the MCSs are determined by the algorithms used for selecting the classifiers, the diversity among the selected classifiers, and the voting method used in the classifier combination. The …

A Ga-Based Adaptive Mechanism For Sensorless Vector Control Of Induction Motor Drives For Urban Electric Vehicles, Asma Boulmane, Youssef Zidani, Driss Belkhayat, Marouane Bouchouirbat

Turkish Journal of Electrical Engineering and Computer Sciences

Induction motors are more attractive to car manufacturers because they are more robust and more cost effective to maintain in comparison with other types of electric machines. The evolution of their control makes them more efficient and less expensive. However, a new control technique known as sensorless control is being used to simplify the implementation of electric machines in electric vehicles. This technique involves replacing the flux and speed sensors with an observer. The estimation of these elements is based on the measurement of currents and voltages. The main purpose of the present study is to design a novel robust …

An Improved Memetic Genetic Algorithm Based On A Complex Network As Asolution To The Traveling Salesman Problem, Hadi Mohammadi, Kamal Mirzaie, Mohammad Reza Mollakhalili Meybodi

Turkish Journal of Electrical Engineering and Computer Sciences

A genetic algorithm (GA) is not a good option for finding solutions around in neighborhoods. The current study applies a memetic algorithm (MA) with a proposed local search to the mutation operator of a genetic algorithm in order to solve the traveling salesman problem (TSP). The proposed memetic algorithm uses swap, reversion and insertion operations to make changes in the solution. In the basic GA, unlike in the real world, the relationship between generations has not been considered. This gap is resolved using the proposed complex network to allow selection among possible solutions. The degree measure has been used for …

Fuzzy Genetic Based Dynamic Spectrum Allocation (Fgdsa) Approach For Cognitive Radio Sensor Networks, Ganesan Rajesh, Xavier Mercilin Raajini, Kulandairaj Martin Sagayam, Bharat Bhushan, Utku Kose

Turkish Journal of Electrical Engineering and Computer Sciences

Cognitive Radio Sensor Network (CRSN) is known as a distributed network of wireless cognitive radio sensor nodes. Such system senses an event signal and ensures collaborative dynamic communication processes over the spectrum bands. Here, the concept of Dynamic Spectrum Access (DSA) denes the method of reaching progressively to the unused range of spectrum band. As among the essential CRSN user types, the Primary User (PU) has the license to access the spectrum band. On the other hand, the Secondary User (SU) tries to access the unused spectrum eciently, by not disturbing the PU. Considering that issue, this study introduces a …

Design, Modeling And Optimization Of Reciprocating Tubular Permanent Magnet Linear Generators For Free Piston Engine Applications, Jayaram Subramanian

Graduate Theses, Dissertations, and Problem Reports

Permanent Magnet Linear Generators (PMLG) are electric generators which convert the linear motion into electricity. One of the applications of the PMLG system is with free piston engines. Here, the piston is moved by the expander using an internal combustion engine or a Stirling engine. Other applications of the PMLG are wave energy conversion, micro energy harvesters, and supercritical CO₂ expander systems. The most common technology of the electric generators is a rotary electric generator. The current technology of the engine-generators (GENSET) is of a rotary type which uses a crankshaft to convert the linear motion to rotary motion …

Smart Distributed Generation System Event Classification Using Recurrent Neural Network-Based Long Short-Term Memory, Shuva Das

Electronic Theses and Dissertations

High penetration of distributed generation (DG) sources into a decentralized power system causes several disturbances, making the monitoring and operation control of the system complicated. Moreover, because of being passive, modern DG systems are unable to detect and inform about these disturbances related to power quality in an intelligent approach. This paper proposed an intelligent and novel technique, capable of making real-time decisions on the occurrence of different DG events such as islanding, capacitor switching, unsymmetrical faults, load switching, and loss of parallel feeder and distinguishing these events from the normal mode of operation. This event classification technique was designed …

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

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

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 …

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 …

Power System Loading Margin Enhancement By Optimal Statcom Integration:A Case Study, Sasidharan Shreedharan, Tibin Joseph, Sebin Joseph, Chittesh Veni Chandran, Vishnu J., Vipin Das P

Articles

Safe and secure network operation with acceptable voltage level has become a challenging task for utilities requiring corrective measures to be implemented. Network upgrades using Flexible Alternating Current Transmission System devices are being considered to serve this purpose. To this end, static loading margin enhancement by optimal static synchronous compensator (STATCOM) allocation to enhance the power transfer capability with minimal voltage variation is presented. Maximum loadability is formulated as an optimization problem, subjected to voltage and small-signal stability constraints. Stability indices are presented and incorporated with the optimization problem to ensure secure operation under maximum loading. The scheme is executed …

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. …

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 …

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, …