Open Access. Powered by Scholars. Published by Universities.®
Physical Sciences and Mathematics Commons™
Open Access. Powered by Scholars. Published by Universities.®
Articles 1 - 15 of 15
Full-Text Articles in Physical Sciences and Mathematics
Development Of A Hybrid System Based On Abc Algorithm For Selection Of Appropriate Parameters For Disease Diagnosis From Ecg Signals, Ersi̇n Ersoy, Gazi̇ Erkan Bostanci, Mehmet Serdar Güzel
Development Of A Hybrid System Based On Abc Algorithm For Selection Of Appropriate Parameters For Disease Diagnosis From Ecg Signals, Ersi̇n Ersoy, Gazi̇ Erkan Bostanci, Mehmet Serdar Güzel
Turkish Journal of Electrical Engineering and Computer Sciences
The number of people who die due to cardiovascular diseases is quite high. In our study, ECG (electrocar-diogram) signals were divided into segments and waves based on temporal boundaries. Signal similarity methods such as convolution, correlation, covariance, signal peak to noise ratio (PNRS), structural similarity index (SSIM), one of the basic statistical parameters, arithmetic mean and entropy were applied to each of these sections. In addition, a square error-based new approach was applied and the difference of the signs from the mean sign was taken and used as a feature vector. The obtained feature vectors are used in the artificial …
A Hybrid Model Based On The Convolutional Neural Network Model And Artificial Bee Colony Or Particle Swarm Optimization-Based Iterative Thresholding For The Detection Of Bruised Apples, Mahmut Heki̇m, Onur Cömert, Kemal Adem
A Hybrid Model Based On The Convolutional Neural Network Model And Artificial Bee Colony Or Particle Swarm Optimization-Based Iterative Thresholding For The Detection Of Bruised Apples, Mahmut Heki̇m, Onur Cömert, Kemal Adem
Turkish Journal of Electrical Engineering and Computer Sciences
In this study, apple images taken with near-infrared (NIR) cameras were classified as bruised and healthy objects using iterative thresholding approaches based on artificial bee colony (ABC) and particle swarm optimization (PSO) algorithms supported by a convolutional neural network (CNN) deep learning model. The proposed model includes the following stages: image acquisition, image preprocessing, the segmentation of anatomical regions (stem-calyx regions) to be discarded, the detection of bruised areas on the apple images, and their classification. For this aim, by using the image acquisition platform with a NIR camera, a total of 1200 images at 6 different angles were taken …
Adaptive Modified Artificial Bee Colony Algorithms (Amabc) For Optimization Ofcomplex Systems, Rabi̇a Korkmaz Tan, Şebnem Bora
Adaptive Modified Artificial Bee Colony Algorithms (Amabc) For Optimization Ofcomplex Systems, Rabi̇a Korkmaz Tan, Şebnem Bora
Turkish Journal of Electrical Engineering and Computer Sciences
Complex systems are large scale and involve numerous uncertainties, which means that such systems tend to be expensive to operate. Further, it is difficult to analyze systems of this kind in a real environment, and for this reason agent-based modeling and simulation techniques are used instead. Based on estimation methods, modeling and simulation techniques establish an output set against the existing input set. However, as the data set in a given complex systems becomes very large, it becomes impossible to use estimation methods to create the output set desired. Therefore, a new mechanism is needed to optimize data sets in …
Adaptive Iir Filter Design Using Self-Adaptive Search Equation Based Artificial Bee Colony Algorithm, Burhanetti̇n Durmuş, Gürcan Yavuz, Doğan Aydin
Adaptive Iir Filter Design Using Self-Adaptive Search Equation Based Artificial Bee Colony Algorithm, Burhanetti̇n Durmuş, Gürcan Yavuz, Doğan Aydin
Turkish Journal of Electrical Engineering and Computer Sciences
Infinite impulse response (IIR) system identification problem is defined as an IIR filter modeling to represent an unknown system. During a modeling task, unknown system parameters are estimated by metaheuristic algorithms through the IIR filter. This work deals with the self-adaptive search-equation-based artificial bee colony (SSEABC) algorithm that is adapted to optimal IIR filter design. SSEABC algorithm is a recent and improved variant of artificial bee colony (ABC) algorithm in which appropriate search equation is determined with a self-adaptive strategy. Moreover, the success of the SSEABC algorithm enhanced with a competitive local search selection strategy was proved on benchmark functions …
Evolutionary Approaches For Weight Optimization In Collaborative Filtering-Based Recommender Systems, Sevgi̇ Yi̇ği̇t Sert, Yilmaz Ar, Gazi̇ Erkan Bostanci
Evolutionary Approaches For Weight Optimization In Collaborative Filtering-Based Recommender Systems, Sevgi̇ Yi̇ği̇t Sert, Yilmaz Ar, Gazi̇ Erkan Bostanci
Turkish Journal of Electrical Engineering and Computer Sciences
Collaborative filtering is one of the widely adopted approaches in recommender systems used for e-commerce applications, stating that users having similar tastes will have similar preferences in the future. The literature presents a number of similarity metrics such as the extended Jaccard coefficient to quantify these preference similarities. This paper aims to improve prediction accuracy by optimizing the similarity values computed using these metrics by adopting two biologically inspired approaches, namely artificial bee colony and genetic algorithms, with a bottom-up approach, suggesting that any improvement on a single-user basis will reflect on the overall prediction accuracy. Detailed statistical analysis was …
Abc-Based Stacking Method For Multilabel Classification, Weimin Ding, Shengli Wu
Abc-Based Stacking Method For Multilabel Classification, Weimin Ding, Shengli Wu
Turkish Journal of Electrical Engineering and Computer Sciences
Multilabel classification is a supervised learning problem wherein each individual instance is associated with multiple labels. Ensemble methods are effective in managing multilabel classification problems by creating a set of accurate, diverse classifiers and then combining their outputs to produce classifications. This paper presents a novel stacking-based ensemble algorithm, ABC-based stacking, for multilabel classification. The artificial bee colony algorithm, along with a single-layer artificial neural network, is used to find suitable meta-level classifier configurations. The optimization goal of the meta-level classifier is to maximize the average accuracy of classification of all the instances involved. We run an experiment on 10 …
Reliable Data Gathering In The Internet Of Things Using Artificial Bee Colony, Samad Najjar-Ghabel, Shamim Yousefi, Leili Farzinvash
Reliable Data Gathering In The Internet Of Things Using Artificial Bee Colony, Samad Najjar-Ghabel, Shamim Yousefi, Leili Farzinvash
Turkish Journal of Electrical Engineering and Computer Sciences
The Internet of Things (IoT) technology enables physical devices to communicate with each other for preparing, gathering, and sharing hazard warnings or critical information without human intervention. With respect to emergency applications of IoT technology, an essential issue is to provide an efficient and robust scheme for data gathering. The proposed solution in the existing approaches is to construct a spanning tree over the IoT devices and collect data using the tree. The shortcoming of these algorithms is that they do not take into account the probability of device mobility or failure. In such cases, the spanning tree is split, …
Optimal Power Flow With Svc Devices By Using The Artificial Bee Colony Algorithm, Kadi̇r Abaci, Volkan Yamaçli, Ali̇ Akdağli
Optimal Power Flow With Svc Devices By Using The Artificial Bee Colony Algorithm, Kadi̇r Abaci, Volkan Yamaçli, Ali̇ Akdağli
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper a simple and efficient heuristic search method based on the artificial bee colony (ABC) algorithm is presented and used for the optimal power flow (OPF) problem in power systems with static VAR compensator (SVC) devices. The total generation cost of a power system with SVC devices (which improve the voltage stability at load buses) is optimally minimized with the use of ABC. The ABC, which is based on the foraging behavior of honey bees searching for the best food source, is a recently proposed optimization algorithm. The performance of the presented ABC algorithm was tested and verified …
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 …
A Hierarchic Approach Based On Swarm Intelligence To Solve The Traveling Salesman Problem, Mesut Gündüz, Mustafa Servet Kiran, Eren Özceylan
A Hierarchic Approach Based On Swarm Intelligence To Solve The Traveling Salesman Problem, Mesut Gündüz, Mustafa Servet Kiran, Eren Özceylan
Turkish Journal of Electrical Engineering and Computer Sciences
The purpose of this paper is to present a new hierarchic method based on swarm intelligence algorithms for solving the well-known traveling salesman problem. The swarm intelligence algorithms implemented in this study are divided into 2 types: path construction-based and path improvement-based methods. The path construction-based method (ant colony optimization (ACO)) produces good solutions but takes more time to achieve a good solution, while the path improvement-based technique (artificial bee colony (ABC)) quickly produces results but does not achieve a good solution in a reasonable time. Therefore, a new hierarchic method, which consists of both ACO and ABC, is proposed …
Optimal Fuzzy Load Frequency Controller With Simultaneous Auto-Tuned Membership Functions And Fuzzy Control Rules, Abas Ali Zamani, Ehsan Bijami, Farid Sheikholeslam, Bahram Jafrasteh
Optimal Fuzzy Load Frequency Controller With Simultaneous Auto-Tuned Membership Functions And Fuzzy Control Rules, Abas Ali Zamani, Ehsan Bijami, Farid Sheikholeslam, Bahram Jafrasteh
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper, an auto-tuned fuzzy load frequency controller (FLFC)-based artificial bee colony (ABC) algorithm is developed to quench the deviations in the frequency and tie-line power due to load disturbances in an interconnected power system. Optimal tuning of membership functions (MFs) and fuzzy control rules is very important to improve the design performance and achieve a satisfactory level of robustness for a particular operation. In this work, to reduce the fuzzy system design effort and take large parametric uncertainties into account, a new systematic and simultaneous tuning method is developed for designing MFs and fuzzy rules. For this, the …
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 …
Xor-Based Artificial Bee Colony Algorithm For Binary Optimization, Mustafa Servet Kiran, Mesut Gündüz
Xor-Based Artificial Bee Colony Algorithm For Binary Optimization, Mustafa Servet Kiran, Mesut Gündüz
Turkish Journal of Electrical Engineering and Computer Sciences
The artificial bee colony (ABC) algorithm, which was inspired by the foraging and dance behaviors of real honey bee colonies, was first introduced for solving numerical optimization problems. When the solution space of the optimization problem is binary-structured, the basic ABC algorithm should be modified for solving this class of problems. In this study, we propose XOR-based modification for the solution-updating equation of the ABC algorithm in order to solve binary optimization problems. The proposed method, named binary ABC (binABC), is examined on an uncapacitated facility location problem, which is a pure binary optimization problem, and the results obtained by …
Artificial Bee Colony Algorithm For Dynamic Deployment Of Wireless Sensor Networks, Celal Öztürk, Dervi̇ş Karaboğa, Beyza Görkemli̇
Artificial Bee Colony Algorithm For Dynamic Deployment Of Wireless Sensor Networks, Celal Öztürk, Dervi̇ş Karaboğa, Beyza Görkemli̇
Turkish Journal of Electrical Engineering and Computer Sciences
As the usage and development of wireless sensor networks increases, problems related to these networks are being discovered. Dynamic deployment is one of the main issues that directly affect the performance of wireless sensor networks. In this paper, an artificial bee colony algorithm is applied to the dynamic deployment of mobile sensor networks to gain better performance by trying to increase the coverage area of the network. The good performance of the algorithm shows that it can be utilized in the dynamic deployment of wireless sensor networks.
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 …