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- Classification (66)
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Articles 2491 - 2520 of 3020
Full-Text Articles in Physical Sciences and Mathematics
Optimal Placement Of Pmus Using Improved Tabu Search For Complete Observability And Out-Of-Step Prediction, Amany El Zonkoly, Samah El Safty, Rana Maher
Optimal Placement Of Pmus Using Improved Tabu Search For Complete Observability And Out-Of-Step Prediction, Amany El Zonkoly, Samah El Safty, Rana Maher
Turkish Journal of Electrical Engineering and Computer Sciences
This paper proposes an optimization method for the optimal placement of phasor measurement units (PMUs) for the complete observability of power systems. The proposed method is based on numerical observability and artificial intelligence. The artificial intelligence algorithm used is the improved tabu search (ITS) algorithm. The ITS is used to find the optimal placement for the PMU to keep the system completely observable. In addition, the paper describes a predictive out-of-step (OOS) algorithm based on the observation of the voltage phase difference between the substations. The proposed optimal placement of the PMUs and the OOS algorithm is tested using the …
Efficient Feature Integration With Wikipedia-Based Semantic Feature Extraction For Turkish Text Summarization, Aysun Güran, Ni̇lgün Güler Bayazit, Mustafa Zahi̇d Gürbüz
Efficient Feature Integration With Wikipedia-Based Semantic Feature Extraction For Turkish Text Summarization, Aysun Güran, Ni̇lgün Güler Bayazit, Mustafa Zahi̇d Gürbüz
Turkish Journal of Electrical Engineering and Computer Sciences
This study presents a novel hybrid Turkish text summarization system that combines structural and semantic features. The system uses 5 structural features, 1 of which is newly proposed and 3 are semantic features whose values are extracted from Turkish Wikipedia links. The features are combined using the weights calculated by 2 novel approaches. The first approach makes use of an analytical hierarchical process, which depends on a series of expert judgments based on pairwise comparisons of the features. The second approach makes use of the artificial bee colony algorithm for automatically determining the weights of the features. To confirm the …
Review Of Distinctive Phonetic Features And The Arabic Share In Related Modern Research, Yousef Alotaibi, Ali Meftah
Review Of Distinctive Phonetic Features And The Arabic Share In Related Modern Research, Yousef Alotaibi, Ali Meftah
Turkish Journal of Electrical Engineering and Computer Sciences
Most research in the field of digital speech technology has traditionally been conducted in only a few languages, such as English, French, Spanish, or Chinese. Numerous studies using distinctive phonetic features (DPFs) with different techniques and algorithms have been carried out during the last 3 decades, mainly in English, Japanese, and other languages of industrialized countries. DPF elements are based on a technique used by linguists and digital speech and language experts to distinguish between different phones by considering the lowest level of actual features during phonation. These studies have investigated the best performances, outcomes, and theories, especially those regarding …
Anticipating The Friction Coefficient Of Friction Materials Used In Automobiles By Means Of Machine Learning Without Using A Test Instrument, Mustafa Ti̇mur, Fati̇h Aydin
Anticipating The Friction Coefficient Of Friction Materials Used In Automobiles By Means Of Machine Learning Without Using A Test Instrument, Mustafa Ti̇mur, Fati̇h Aydin
Turkish Journal of Electrical Engineering and Computer Sciences
The most important factor for designs in which friction materials are used is the coefficient of friction. The coefficient of friction has been determined taking such variants as velocity, temperature, and pressure into account, which arise from various factors in friction materials, and by analyzing the effects of these variants on friction materials. Many test instruments have been produced in order to determine the coefficient of friction. In this article, a study about the use of machine learning algorithms instead of test instruments in order to determine the coefficient of friction is presented. Isotonic regression was selected as the machine …
A Linearly Slotted Waveguide Antenna And Comparison Of It With A Sinusoidal One, Alp Oral Salman
A Linearly Slotted Waveguide Antenna And Comparison Of It With A Sinusoidal One, Alp Oral Salman
Turkish Journal of Electrical Engineering and Computer Sciences
A linearly slotted waveguide antenna (LSWA) is investigated. The slot is placed in one of the narrow faces of a rectangular waveguide, which operates at Ka-band (26.5--40 GHz), which is in a frequency range including upper microwaves and the lower edge of millimeter waves. Analytically, the magnetic current approach is applied. Some antenna parameters of this structure are experimentally measured and it is observed that the antenna radiates a single transversal-polarized beam that scans with frequency. The experimentally obtained patterns in 2 perpendicular planes are also correlated with analytical and numerical patterns that use the magnetic current model and HFSS, …
A Learning Approach In Link Adaptation For Mimo-Ofdm Systems, Hali̇l Yi̇ği̇t, Adnan Kavak
A Learning Approach In Link Adaptation For Mimo-Ofdm Systems, Hali̇l Yi̇ği̇t, Adnan Kavak
Turkish Journal of Electrical Engineering and Computer Sciences
We propose a neural network (NN)-based adaptive modulation and coding (AMC) for link adaptation in MIMO-OFDM systems. The AMC optimizes the best modulation and coding scheme (MCS) under a packet error rate (PER) constraint. In our approach, a NN with a multilayer perceptron (MLP) structure is applied for the AMC and its performance is compared with the k-nearest neighbor (k-NN) algorithm under the frequency-flat (1-tap) and frequency-selective (4-tap) wireless channel conditions. The simulation results show that the NN classifier outperforms the k-NN algorithm, especially in terms of the PER, due to the fact that the MLP guarantees a MCS with …
Optimized Features Selection For Gender Classification Using Optimization Algorithms, Sajid Ali Khan, Muhammad Nazir, Naveed Riaz
Optimized Features Selection For Gender Classification Using Optimization Algorithms, Sajid Ali Khan, Muhammad Nazir, Naveed Riaz
Turkish Journal of Electrical Engineering and Computer Sciences
Optimized feature selection is an important task in gender classification. The optimized features not only reduce the dimensions, but also reduce the error rate. In this paper, we have proposed a technique for the extraction of facial features using both appearance-based and geometric-based feature extraction methods. The extracted features are then optimized using particle swarm optimization (PSO) and the bee algorithm. The geometric-based features are optimized by PSO with ensemble classifier optimization by the genetic algorithm. Using this approach, we have obtained promising results in terms of the classification error rate and computation time minimization. Moreover, our optimized feature-based method …
Economic Power Dispatch Of Power Systems With Pollution Control Using Artificial Bee Colony Optimization, Linda Slimani, Tarek Bouktir
Economic Power Dispatch Of Power Systems With Pollution Control Using Artificial Bee Colony Optimization, Linda Slimani, Tarek Bouktir
Turkish Journal of Electrical Engineering and Computer Sciences
This paper presents a solution for the emission-controlled economic dispatch (ECED) problem of medium-sized power systems via an artificial bee colony algorithm. The ECED problem, which accounts for the minimization of both the fuel cost and the emission, is a multiple objective function problem. The objective is to minimize the total fuel cost of the generation and environmental pollution caused by fossil-based thermal generating units and to also maintain an acceptable system performance in terms of the limits on the generator's real and reactive power outputs, bus voltages, shunt capacitors/reactors, and power flow of transmission lines. The proposed algorithm is …
Classification Of Power Quality Disturbances Using S-Transform And Tt-Transform Based On The Artificial Neural Network, Sajad Jashfar, Saeed Esmaeili, Mehdi Zareian Jahromi, Mohsen Rahmanian
Classification Of Power Quality Disturbances Using S-Transform And Tt-Transform Based On The Artificial Neural Network, Sajad Jashfar, Saeed Esmaeili, Mehdi Zareian Jahromi, Mohsen Rahmanian
Turkish Journal of Electrical Engineering and Computer Sciences
The classification of power quality (PQ) disturbances to improve the PQ is an important issue in utilities and industrial factories. In this paper, an approach to classify PQ disturbances is presented. First, a signal containing one of the PQ disturbances, like sag, swell, flicker, interruption, transient, or harmonics, is evaluated using the proposed approach. Afterwards, S-transform and TT-transform are applied to the signal and an artificial neural network is used to recognize the disturbance using S-transform and TT-transform data, like the variance and mean values of S-transform and TT-transform matrices. The main features of the proposed approach are the real-time …
High-Performance Cmos Cci In A 0.35 \Mu M Cmos Technology And A New All-Pass Filter Application, Emre Arslan, Bi̇lgi̇n Meti̇n, Mehmet Oğuzhan Çi̇çekoğlu, Avni̇ Morgül
High-Performance Cmos Cci In A 0.35 \Mu M Cmos Technology And A New All-Pass Filter Application, Emre Arslan, Bi̇lgi̇n Meti̇n, Mehmet Oğuzhan Çi̇çekoğlu, Avni̇ Morgül
Turkish Journal of Electrical Engineering and Computer Sciences
A differential pair-based, high-performance, first-generation current conveyor is proposed. The proposed circuit is laid out using the Mentor Graphics IC Station layout editor. The performance characteristics have been determined from HSpice postlayout simulations using the Austria Mikro Systeme 0.35 \mu m, 3.3 V process parameters. During the simulations, \pm 1.65 V supply voltages and a 25 \mu A biasing current are used. The power consumption is about 1.12 mW. The circuit also has very high voltage swings on ports X and Y, a very small impedance value on port X, high impedance values on ports Y and Z, and high-valued …
A Novel Uwb Cpw-Fed Ring-Shaped Antenna With Band-Notched Characteristics, Maryam Majidzadeh, Changiz Ghobadi
A Novel Uwb Cpw-Fed Ring-Shaped Antenna With Band-Notched Characteristics, Maryam Majidzadeh, Changiz Ghobadi
Turkish Journal of Electrical Engineering and Computer Sciences
A novel compact omnidirectional coplanar waveguide (CPW)-fed antenna with band-notched characteristics has been designed and analyzed. The proposed ultra-wideband (UWB) antenna has a simple structure. A ring-shaped radiating patch is excited by a CPW feed line. By creating 2 square slots on the top corners of the antenna, a new resonance is excited and the bandwidth is enhanced. The band-notched function is achieved by applying 2 rectangular stubs to the ground plane structure. The proposed antenna occupies a small size of 20 x 20 x 1 mm^3 and covers a wide frequency range of 3.1--14 GHz, except for 5--6 GHz, …
Opposition-Based Discrete Action Reinforcement Learning Automata Algorithm Case Study: Optimal Design Of A Pid Controller, Fatemeh Mohseni Pour, Ali Akbar Gharaveisi
Opposition-Based Discrete Action Reinforcement Learning Automata Algorithm Case Study: Optimal Design Of A Pid Controller, Fatemeh Mohseni Pour, Ali Akbar Gharaveisi
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper, the discrete action reinforcement learning automata (DARLA) method is expressed. The performance of the reinforcement learning algorithm is improved using the opposite concepts. This is an automatic method that can find the global optima without any knowledge about the parameters of the research space. To find the global optimal point, the interval that contains the optima is determined by DARLA as the cost function is minimized. In the opposition-based DARLA method, learning is performed based on opposition. The main idea in the opposition is to consider the search direction and its opposite at the same time to …
K-Means Algorithm With A Novel Distance Measure, Shadi Abudalfa, Mohammad Mikki
K-Means Algorithm With A Novel Distance Measure, Shadi Abudalfa, Mohammad Mikki
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper, we describe an essential problem in data clustering and present some solutions for it. We investigated using distance measures other than Euclidean type for improving the performance of clustering. We also developed an improved point symmetry-based distance measure and proved its efficiency. We developed a k-means algorithm with a novel distance measure that improves the performance of the classical k-means algorithm. The proposed algorithm does not have the worst-case bound on running time that exists in many similar algorithms in the literature. Experimental results shown in this paper demonstrate the effectiveness of the proposed algorithm. We compared …
Interaction Analysis Of Multi-Function Facts And D-Facts Controllers By Mrga, Maghsood Mokhtari, Javad Khazaie, Daryoush Nazarpour, Morteza Farsadi
Interaction Analysis Of Multi-Function Facts And D-Facts Controllers By Mrga, Maghsood Mokhtari, Javad Khazaie, Daryoush Nazarpour, Morteza Farsadi
Turkish Journal of Electrical Engineering and Computer Sciences
With the growing application of flexible AC transmission systems (FACTS) and distributed FACTS (D-FACTS), the coordinating problem of FACTS and D-FACTS controllers in joint operation must be considered in modern power systems. The main purpose of this paper is to investigate the possible interaction that may occur between the distributed static series compensator (DSSC) and the static synchronous compensator (STATCOM) when they operate concurrently in the power system. The modified relative gain array (MRGA) is implemented to analyze the interactions. The application of MRGA for the effective design of multiobjective controllers of the STATCOM and DSSC is demonstrated by 2 …
Performance Evolution Of A Newly Developed General-Use Hybrid Ais-Ann System: Aaa-Response, Seral Özşen, Sali̇h Güneş
Performance Evolution Of A Newly Developed General-Use Hybrid Ais-Ann System: Aaa-Response, Seral Özşen, Sali̇h Güneş
Turkish Journal of Electrical Engineering and Computer Sciences
In this study, we have developed a nonlinear recognition system in the artificial immune systems (AIS) field named `AaA-response (artificial neural network (ANN)-aided AIS-response)', which is different from previous AIS methods in that it uses a different modeling strategy in the formation of the memory response. Because it also uses ANNs in the determination of the correct output, it can be seen as a hybrid system that involves AIS and ANN approaches. Unlike the other AIS methods, AaA-response uses multiple system units (or antibodies) to form an output for a presented input. This property gives the proposed system the ability …
Discrete Event Simulation-Based Performance Evaluation Of Internet Routing Protocols, Fati̇h Çeli̇k, Ahmet Zengi̇n, Bülent Çobanoğlu
Discrete Event Simulation-Based Performance Evaluation Of Internet Routing Protocols, Fati̇h Çeli̇k, Ahmet Zengi̇n, Bülent Çobanoğlu
Turkish Journal of Electrical Engineering and Computer Sciences
This paper presents a discrete event system specification (DEVS)-based comparative performance analysis between the open shortest path first (OSPF) protocol and the routing information protocol (RIP), together with the border gateway protocol (BGP), using DEVS-Suite. In order to evaluate the OSPF and RIP's scalability performance, several network models are designed and configured with the OSPF and RIP, in combination with the BGP. Evaluations of the proposed routing protocols are performed based on the metrics, such as the execution time, convergence time, turnaround time, throughput, and efficiency across an increasing size and complexity through the simulated network models. The evaluation results …
Hybrid Of Genetic Algorithm And Great Deluge Algorithm For Rough Set Attribute Reduction, Najmeh Sadat Jaddi, Salwani Abdullah
Hybrid Of Genetic Algorithm And Great Deluge Algorithm For Rough Set Attribute Reduction, Najmeh Sadat Jaddi, Salwani Abdullah
Turkish Journal of Electrical Engineering and Computer Sciences
The attribute reduction problem is the process of reducing unimportant attributes from a decision system to decrease the difficulty of data mining or knowledge discovery tasks. Many algorithms have been used to optimize this problem in rough set theory. The genetic algorithm (GA) is one of the algorithms that has already been applied to optimize this problem. This paper proposes 2 kinds of memetic algorithms, which are a hybridization of the GA, with 2 versions (linear and nonlinear) of the great deluge (GD) algorithm. The purpose of this hybridization is to investigate the ability of this local search algorithm to …
Cada: Channel And Delay Aware Scheduler For Real-Time Applications In Wimax Networks, Melek Oktay, Haci Ali̇ Mantar
Cada: Channel And Delay Aware Scheduler For Real-Time Applications In Wimax Networks, Melek Oktay, Haci Ali̇ Mantar
Turkish Journal of Electrical Engineering and Computer Sciences
Scheduling is the core of the worldwide interoperability for microwave access (WiMAX) technology that directly affects the performance of the network. In this study, we focus on scheduling and present a novel algorithm called the channel and delay aware scheduler (CADA) for real-time applications, such as voice over Internet protocol, video-on-demand, and video streaming. CADA has 2 important modules: wireless and network delay monitoring tools. The wireless module, including the compensation and channel state monitoring modules, increases the network throughput and provides fairness among all of the flows in the network. The network delay monitoring tool calculates the estimated network …
Estimation Of Fuel Cost Curve Parameters For Thermal Power Plants Using The Abc Algorithm, Yusuf Sönmez
Estimation Of Fuel Cost Curve Parameters For Thermal Power Plants Using The Abc Algorithm, Yusuf Sönmez
Turkish Journal of Electrical Engineering and Computer Sciences
The solution accuracy of economic dispatch problems is associated with the accuracy of the fuel cost curve parameters. Therefore, updating of these parameters is a very important issue to further improve the final accuracy of economic dispatch problems. Estimating the parameters of the fuel cost curve may be the best solution for this issue. This paper presents an application of the artificial bee colony (ABC) algorithm to estimate the fuel cost curve parameters of thermal power plants. In the estimation problem, 1st-, 2nd-, and 3rd-order fuel cost functions are used, and the estimation problem is formulated as an optimization one. …
Improving Power Systems Operation Through Multiobjective Optimal Location Of Optimal Unified Power Flow Controller, Afshin Lashkar Ara, Ahad Kazemi, Mohammad Behshad
Improving Power Systems Operation Through Multiobjective Optimal Location Of Optimal Unified Power Flow Controller, Afshin Lashkar Ara, Ahad Kazemi, Mohammad Behshad
Turkish Journal of Electrical Engineering and Computer Sciences
This paper presents a multiobjective optimization methodology to find the optimal location for an optimal unified power flow controller (OUPFC) device. Moreover, the installation cost function of the OUPFC device is developed. The objective functions are the total fuel cost, power losses, and system loadability with and without the minimum cost of the OUPFC installation. The \varepsilon-constraint approach is implemented for the multiobjective mathematical programming formulation. The proposed algorithm is implemented in the IEEE 30- and 118-bus test systems. The solution procedure uses nonlinear programming to optimally locate the OUPFC incorporated in an optimal power flow problem considering these objective …
Optimal Iterative Learning Control Design For Generator Voltage Regulation System, Mohsen Rezaei Estakhrouieh, Ali Akbar Gharaveisi
Optimal Iterative Learning Control Design For Generator Voltage Regulation System, Mohsen Rezaei Estakhrouieh, Ali Akbar Gharaveisi
Turkish Journal of Electrical Engineering and Computer Sciences
The purpose of this paper is to design a good tracking controller for the generator automatic voltage regulator (AVR) system. It uses an iterative learning control (ILC) algorithm as a control rule and tries to keep voltage error as low as possible, while replying to set point changes as fast as possible. Two models of ILC are discussed: P-type learning and linear quadratic (LQ) optimal design. The results of designing by LQ optimal method are compared with a Ziegler--Nichols proportional-integral-derivative (PID) controller. The effects of changing different parameters are investigated and illustrated by simulation. In order to provide better robustness …
Using The Csm And Vsm Techniques To Speed Up The Ica Algorithm Without A Loss Of Quality, Mahdi Mahdikhani, Mohammad Hosein Kahaei
Using The Csm And Vsm Techniques To Speed Up The Ica Algorithm Without A Loss Of Quality, Mahdi Mahdikhani, Mohammad Hosein Kahaei
Turkish Journal of Electrical Engineering and Computer Sciences
In blind source separation problems that are implemented based on the independent component analysis (ICA) algorithm, the separation speed and quality are related inversely. In this paper, the proposed algorithms eliminate this tradeoff by generating a faster separation while maintaining the quality. In the proposed algorithms, in each frequency bin and in all of the learning steps, the separation quality of the separating matrix is compared with another one that we define as a situated matrix, and the best matrix is considered as an initial separating matrix in the next learning step. In this paper, we propose 2 algorithms based …
Simulation Of Discrete Electromagnetic Propagation Model For Atmospheric Effects On Mobile Communication, Şaban Seli̇m Şeker, Fulya Kunter
Simulation Of Discrete Electromagnetic Propagation Model For Atmospheric Effects On Mobile Communication, Şaban Seli̇m Şeker, Fulya Kunter
Turkish Journal of Electrical Engineering and Computer Sciences
Wireless communication has become an important part of our lives, and atmospheric effects are one of the ultimate factors affecting quality of communication and satellite systems. In this study the attenuation in mobile communication due to atmospheric events like snow and rain is simulated using the discrete propagation model. In this work, spherical raindrop and oblate spheroid raindrop modeling are used. To check the validity of simulations, the commonly used and accepted ITU-R rain model is used. Oblate spheroid raindrop modeling produces results that are more compatible with ITU-R results, especially at frequencies higher than 50 GHz. At lower frequencies, …
Fuzzified Artificial Bee Colony Algorithm For Nonsmooth And Nonconvex Multiobjective Economic Dispatch Problem, Chandrasekaran Koodalsamy, Sishaj Pulikottil Simon
Fuzzified Artificial Bee Colony Algorithm For Nonsmooth And Nonconvex Multiobjective Economic Dispatch Problem, Chandrasekaran Koodalsamy, Sishaj Pulikottil Simon
Turkish Journal of Electrical Engineering and Computer Sciences
The economic dispatch (ED) problem is one of the important optimization problems in power system operation. Recently the power system has stressed the need for reliable, nonpolluting, and economic operation. Hence, 3 conflicting functions of reliability, emission, and fuel cost are considered in the objective function of the proposed ED problem. The problem is formulated as a nonsmooth and nonconvex problem when the valve-point effects of thermal units are considered in the proposed reliable emission and economic dispatch (REED) problem. This paper presents a multiobjective optimization methodology for solving the newly developed REED problem using a fuzzified artificial bee colony …
An Efficient Solving Of The Traveling Salesman Problem: The Ant Colony System Having Parameters Optimized By The Taguchi Method, Musa Peker, Baha Şen, Pinar Yildiz Kumru
An Efficient Solving Of The Traveling Salesman Problem: The Ant Colony System Having Parameters Optimized By The Taguchi Method, Musa Peker, Baha Şen, Pinar Yildiz Kumru
Turkish Journal of Electrical Engineering and Computer Sciences
Owing to its complexity, the traveling salesman problem (TSP) is one of the most intensively studied problems in computational mathematics. The TSP is defined as the provision of minimization of total distance, cost, and duration by visiting the n number of points only once in order to arrive at the starting point. Various heuristic algorithms used in many fields have been developed to solve this problem. In this study, a solution was proposed for the TSP using the ant colony system and parameter optimization was taken from the Taguchi method. The implementation was tested by various data sets in the …
Discovery Of The Connection Among Age-Related Macular Degeneration, Mthfr C677t And Pai 1 4g/5g Gene Polymorphisms, And Body Mass Index By Means Of Bayesian Inference Methods, Aydan Çelebi̇ler, Huseyin Seker, Bora Yüksel, Ahmet Orun, Si̇bel Bi̇lgi̇li̇, Muhammet Baysal Karaca
Discovery Of The Connection Among Age-Related Macular Degeneration, Mthfr C677t And Pai 1 4g/5g Gene Polymorphisms, And Body Mass Index By Means Of Bayesian Inference Methods, Aydan Çelebi̇ler, Huseyin Seker, Bora Yüksel, Ahmet Orun, Si̇bel Bi̇lgi̇li̇, Muhammet Baysal Karaca
Turkish Journal of Electrical Engineering and Computer Sciences
Age-related macular degeneration (AMD) is the leading cause of irreversible blindness in the elderly. The aim of this study was therefore to explore the relationship between the presence of multiple gene polymorphisms and 2 distinct advanced `dry and wet' AMD phenotypes, and to assess gene interactions with the influence of personal factors in a Turkish population as a pilot study. For the analysis, the data were collected from 73 unrelated participants, grouped as 29 wet and 26 dry AMD patients, and 18 healthy controls. They were all genotyped for the multiple gene polymorphisms in 12 different genes. The data set …
A New Intelligent Classifier For Breast Cancer Diagnosis Based On A Rough Set And Extreme Learning Machine: Rs + Elm, Yilmaz Kaya
A New Intelligent Classifier For Breast Cancer Diagnosis Based On A Rough Set And Extreme Learning Machine: Rs + Elm, Yilmaz Kaya
Turkish Journal of Electrical Engineering and Computer Sciences
Breast cancer is one of the leading causes of death among women all around the world. Therefore, true and early diagnosis of breast cancer is an important problem. The rough set (RS) and extreme learning machine (ELM) methods were used collectively in this study for the diagnosis of breast cancer. The unnecessary attributes were discarded from the dataset by means of the RS approach. The classification process by means of ELM was performed using the remaining attributes. The Wisconsin Breast Cancer dataset (WBCD), derived from the University of California Irvine machine learning database, was used for the purpose of testing …
Swarm Optimization Tuned Mamdani Fuzzy Controller For Diabetes Delayed Model, Mohammad Hassan Khooban, Davood Nazari Maryam Abadi, Alireza Alfi, Mehdi Siahi
Swarm Optimization Tuned Mamdani Fuzzy Controller For Diabetes Delayed Model, Mohammad Hassan Khooban, Davood Nazari Maryam Abadi, Alireza Alfi, Mehdi Siahi
Turkish Journal of Electrical Engineering and Computer Sciences
Diabetes is a chronic disease in which there are high levels of sugar in the blood. Insulin is a hormone that regulates the blood glucose level in the body. Diabetes mellitus can be caused by too little insulin, a resistance to insulin, or both. Although research activities on controlling blood glucose have been attempted to lower the blood glucose level in the quickest possible time, there are some shortages in the amount of the insulin injection. In this paper, a complete model of the glucose--insulin regulation system, which is a nonlinear delay differential model, is used. The purpose of this …
Prediction Of Emissions And Exhaust Temperature For Direct Injection Diesel Engine With Emulsified Fuel Using Ann, Görkem Kökkülünk, Erhan Akdoğan, Vezi̇r Ayhan
Prediction Of Emissions And Exhaust Temperature For Direct Injection Diesel Engine With Emulsified Fuel Using Ann, Görkem Kökkülünk, Erhan Akdoğan, Vezi̇r Ayhan
Turkish Journal of Electrical Engineering and Computer Sciences
Exhaust gases have many effects on human beings and the environment. Therefore, they must be kept under control. The International Convention for the Prevention of Pollution from Ships (MARPOL), which is concerned with the prevention of marine pollution, limits the emissions according to the regulations. In Emission Control Area (ECA) regions, which are determined by MARPOL as ECAs, the emission rates should be controlled. Direct injection (DI) diesel engines are commonly used as a propulsion system on ships. The prediction and control of diesel engine emission rates is not an easy task in real time. Therefore, in this study, an …
Power Efficient Linear Transmitters Using Sigma-Delta Modulation With Switching Amplifiers, Tayfun Nesimoglu
Power Efficient Linear Transmitters Using Sigma-Delta Modulation With Switching Amplifiers, Tayfun Nesimoglu
Turkish Journal of Electrical Engineering and Computer Sciences
In conventional envelope elimination and restoration transmitters, the envelope information of the carrier is reconstructed by modulating the supply voltage of the switching amplifier. In this paper, it is shown that the supply voltage modulation introduces nonlinearity and reduces the average power efficiency of the transmitter. Here, novel transmitter architectures using sigma-delta--modulated carrier signals are proposed to overcome these shortcomings. The proposed architecture's and conventional envelope elimination and restoration transmitter's linearity and efficiency performances are compared at various oversampling rates and signal bandwidths. It is demonstrated that the proposed architectures may provide better linearity and efficiency than conventional envelope elimination …