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Computer Engineering

2013

Genetic algorithm

Articles 1 - 8 of 8

Full-Text Articles in Physical Sciences and Mathematics

Symbol Detection Using The Differential Evolution Algorithm In Mimo-Ofdm Systems, Muhammet Nuri̇ Seyman, Necmi̇ Taşpinar Jan 2013

Symbol Detection Using The Differential Evolution Algorithm In Mimo-Ofdm Systems, Muhammet Nuri̇ Seyman, Necmi̇ Taşpinar

Turkish Journal of Electrical Engineering and Computer Sciences

Channel estimation and symbol detection in multiple-input and multiple-output (MIMO)-orthogonal frequency division multiplexing (OFDM) systems are essential tasks. Although the maximum likelihood (ML) detector reveals excellent performance for symbol detection, the computational complexity of this algorithm is extremely high in systems with more transmitter antennas and high-order constellation size. In this paper, we propose the differential evolution (DE) algorithm in order to reduce the search space of the ML detector and the computational complexity of symbol detection in MIMO-OFDM systems. The DE algorithm is also compared to some heuristic approaches, such as the genetic algorithm and particle swarm optimization. According …


Bidding Strategy Of Generation Companies In A Competitive Electricity Market Using The Shuffled Frog Leaping Algorithm, Vijaya Kumar Jonnalagadda, Vinod Kumar Dulla Mallesham Jan 2013

Bidding Strategy Of Generation Companies In A Competitive Electricity Market Using The Shuffled Frog Leaping Algorithm, Vijaya Kumar Jonnalagadda, Vinod Kumar Dulla Mallesham

Turkish Journal of Electrical Engineering and Computer Sciences

In a competitive electricity market, generation companies need suitable bidding models to maximize their profit. Therefore, each supplier will bid strategically for choosing the bidding coefficients to counter the competitors' bidding strategies. In this paper, the optimal bidding strategy problem is solved using a novel algorithm based on the shuffled frog leaping algorithm (SFLA). It is a memetic metaheuristic that is designed to seek a global optimal solution by performing a heuristic search. It combines the benefits of the genetic-based memetic algorithm (MA) and the social behavior-based particle swarm optimization (PSO). This allows it to have a more precise search …


A New Method Based On Sensitivity Analysis To Optimize The Placement Of Ssscs, Hamed Hashemi Dezaki, Masoud Mohammadalizadeh Shabestary, Hossein Askarian Abyaneh, Gevorg Babamalek Gharehpetian, Mehdi Garmrudi Jan 2013

A New Method Based On Sensitivity Analysis To Optimize The Placement Of Ssscs, Hamed Hashemi Dezaki, Masoud Mohammadalizadeh Shabestary, Hossein Askarian Abyaneh, Gevorg Babamalek Gharehpetian, Mehdi Garmrudi

Turkish Journal of Electrical Engineering and Computer Sciences

The flexible altering current transmission system (FACTS) controllers such as static synchronous series compensators (SSSCs) and unified power flow controllers can strongly improve the different parameters of power systems. They can be used to improve the transient stabilities, voltage profiles, lines transmission capabilities, etc. Therefore, the optimized allocation of FACTS devices is an important issue in recent research. The optimal placements of FACTS devices can have a determinant effect on the performance of a system, too. In this paper, the proper allocation of SSSCs is proposed. Sensitivity analysis is used in order to model SSSCs' effects on the power system. …


Optimized Operation And Maintenance Costs To Improve System Reliability By Decreasing The Failure Rate Of Distribution Lines, Hamed Hashemi Dezaki, Seyed Hossein Hosseinian, Hossein Askarian Abyaneh, Seyed Mohammad Mousavi Agah Jan 2013

Optimized Operation And Maintenance Costs To Improve System Reliability By Decreasing The Failure Rate Of Distribution Lines, Hamed Hashemi Dezaki, Seyed Hossein Hosseinian, Hossein Askarian Abyaneh, Seyed Mohammad Mousavi Agah

Turkish Journal of Electrical Engineering and Computer Sciences

Improving distribution system reliability has received a great deal of attention in recent years. Because of the limitation in expected budgets, it is desirable to determine the most efficient strategy to improve system reliability. This paper proposes a novel method to determine the optimized operation and maintenance costs in order to decrease the failure of system components. The proposed objective function includes the average system frequency interruption index (ASIFI) value. To achieve the best strategy to decrease failures of system components, it is necessary to find the minimum value of the objective function, considering the constraints of operation and maintenance …


Optimal Sizing And Siting Distributed Generation Resources Using A Multiobjective Algorithm, Seyed Amir Hosseini, Seyed Siavash Karimi Madahi, Farzad Razavi, Mohsen Karami, Ali Asghar Ghadimi Jan 2013

Optimal Sizing And Siting Distributed Generation Resources Using A Multiobjective Algorithm, Seyed Amir Hosseini, Seyed Siavash Karimi Madahi, Farzad Razavi, Mohsen Karami, Ali Asghar Ghadimi

Turkish Journal of Electrical Engineering and Computer Sciences

The restructuring of the electrical market, improvement in the technologies of energy production, and energy crisis have paved the way for increasing applications of distributed generation (DG) resources in recent years. Installing DG units in a distribution network may result in positive impacts, such as voltage profile improvement and loss reduction, and negative impacts, such as an increase in the short-circuit level. These impacts depend on the type, capacity, and place of these resources. Therefore, finding the optimal place and capacity of DG resources is of crucial importance. Accordingly, this paper is aimed at finding the optimal place and capacity …


Solution To The Unit Commitment Problem Using An Artificial Neural Network, Mehdi Zareian Jahromi, Mohammad Mehdi Hosseini Bioki, Masoud Rashidi Nejad, Roohollah Fadaeinedjad Jan 2013

Solution To The Unit Commitment Problem Using An Artificial Neural Network, Mehdi Zareian Jahromi, Mohammad Mehdi Hosseini Bioki, Masoud Rashidi Nejad, Roohollah Fadaeinedjad

Turkish Journal of Electrical Engineering and Computer Sciences

This paper proposes a real-time solution to the unit commitment problem by considering different constraints like ramp-up rate, unit operation emissions, next hours load, and minimum down time. In this method, an optimized trade-off between cost and emission has been taken into consideration. The effectiveness of the proposed method was verified by the significant outcomes demonstrated.


Hybrid Of Genetic Algorithm And Great Deluge Algorithm For Rough Set Attribute Reduction, Najmeh Sadat Jaddi, Salwani Abdullah Jan 2013

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 …


Optimized Features Selection For Gender Classification Using Optimization Algorithms, Sajid Ali Khan, Muhammad Nazir, Naveed Riaz Jan 2013

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 …