• International Journal of Fuzzy Logic and Intelligent Systems
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• v.5 no.3
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• pp.206-215
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• 2005

In this paper, we propose a new design method of Genetic Algorithm Processor(GAP) and Evolvable Hardware(EHW). All sorts of creature evolve its structure or shape in order to adapt itself to environments. Evolutionary Computation based on the process of natural selection not only searches the quasi-optimal solution through the evolution process, but also changes the structure to get best results. On the other hand, Genetic Algorithm(GA) is good fur finding solutions of complex optimization problems. However, it has a major drawback, which is its slow execution speed when is implemented in software of a conventional computer. Parallel processing has been one approach to overcome the speed problem of GA. In a point of view of GA, long bit string length caused the system of GA to spend much time that clear up the problem. Evolvable Hardware refers to the automation of electronic circuit design through artificial evolution, and is currently increased with the interested topic in a research domain and an engineering methodology. The studies of EHW generally use the XC6200 of Xilinx. The structure of XC6200 can configure with gate unit. Each unit has connected up, down, right and left cell. But the products can't use because had sterilized. So this paper uses Vertex-E (XCV2000E). The cell of FPGA is made up of Configuration Logic Block (CLB) and can't reconfigure with gate unit. This paper uses Vertex-E is composed of the component as cell of XC6200 cell in VertexE

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.16 no.1 s.92
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• pp.40-48
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• 2005

In this paper, we explore the inductively coupled concept and propose a class of electrically small planar antennas. The antennas are optimized using NEC in conjunction with a Pareto GA. These antennas show good efficiency and bandwidth performance without any additional matching network. Several optimized designs are fabricated and measured. We explain the operating principle of these antennas using a simple lumped element circuit model. The proposed antennas are translated as printed lines on Duroid for RFID tag antennas.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.19 no.1
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• pp.143-147
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• 2005

In this paper, an axial type brushless DC motor which has double rotors using rare-earth magnet pieces is designed. This kind of motor has shorter axial length and is easier to assemble than the radial type motors. To get enough torque, NdFeB magnet is used and for the cost of production, the magnets are segmented to rectangle or disk shape. To design this motor, a equivalent circuit is adopted and the air-gap density is calculated using 3D finite element method to get exact parameters. The design variables are optimized with genetic algorithm. From the results of the simulations, the reference of the axial type BLDC motors can be obtained.

• Journal of Electrical Engineering and Technology
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• v.13 no.5
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• pp.1864-1873
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• 2018

Energy shifting is an innovative method used to obtain the highest profit from the operation of energy storage systems (ESS) by controlling the charge and discharge schedules according to the electricity prices in a given period. Therefore, in this study, we propose an optimal charge and discharge scheduling method that performs energy shift operations derived from an ESS efficiency model. The efficiency model reflects the construction of power conversion systems (PCSs) and lithium battery systems (LBSs) according to the rated discharge time of a MWh-scale ESS. The PCS model was based on measurement data from a real system, whereas for the LBS, we used a circuit model that is appropriate for the MWh scale. In addition, this paper presents the application of a genetic algorithm to obtain the optimal charge and discharge schedules. This development represents a novel evolutionary computation method and aims to find an optimal solution that does not modify the total energy volume for the scheduling process. This optimal charge and discharge scheduling method was verified by various case studies, while the model was used to realize a higher profit than that realized using other scheduling methods.

• Journal of Power Electronics
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• v.15 no.4
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• pp.1119-1130
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• 2015

This study investigates the multi-objective fuzzy optimization of crowbar resistance for the doubly fed induction generator (DFIG) low-voltage ride-through (LVRT). By integrating the crowbar resistance of the crowbar circuit as a decision variable, a multi-objective model for crowbar resistance value optimization has been established to minimize rotor overcurrent and to simultaneously reduce the DFIG reactive power absorbed from the grid during the process of LVRT. A multi-objective genetic algorithm (MOGA) is applied to solve this optimization problem. In the proposed GA, the value of the crowbar resistance is represented by floating-point numbers in the GA population. The MOGA emphasizes the non-dominated solutions and simultaneously maintains diversity in the non-dominated solutions. A fuzzy-set-theory-based is employed to obtain the best solution. The proposed approach has been evaluated on a 3 MW DFIG LVRT. Simulation results show the effectiveness of the proposed approach for solving the crowbar resistance multi-objective optimization problem in the DFIG LVRT.

• Journal of information and communication convergence engineering
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• v.19 no.2
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• pp.114-119
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• 2021

This paper proposes a method to find an optimal T' with the most terminal of the subset of T' trees that can be connected by a given length by improving a memetic genetic algorithm within several constraints, when the set of terminal T is given to the Euclidean plane R². Constraint (1) is that a given length cannot connect all terminals of T, and (2) considers only the rectilinear layout of the edge connecting each terminal. The construction of interconnections has been used in various design-related areas, from network to architecture. Among these areas, there are cases where only the rectilinear layout is considered, such as wiring paths in the computer network and VLSI design, network design, and circuit connection length estimation in standard cell deployment. Therefore, the heuristics proposed in this paper are expected to provide various cost savings in the rectilinear layout.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.44 no.3 s.357
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• pp.26-32
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• 2007

A simple but accurate equivalent circuit of an aperture-coupled cavity-fed microstrip patch antenna is developed. It consists of ideal transformers, admittance elements, and transmission lines, and the related circuit element values are computed by applying the reciprocity theorem and complex power concept with the spectral-domain immittance approach. After validating by the published design example, a dual-band antenna was designed with the help of a hybrid optimization method. For this purpose, the Genetic Algorithm is applied with the Nelder-Mead simplex method. The obtained good results show that this approach turned out to be a very efficient tool for the design of aperture-coupled cavity-fed microstrip patch antenna having various structural design parameters.

• Journal of Electrical Engineering and Technology
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• v.11 no.6
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• pp.1590-1599
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• 2016

The installation of distributed generation (DG) in the electrical networks has numerous advantages. However, connecting and disconnecting of DGs (CADD) leads to some problems in coordination of protection devices due to the changes in the short circuit levels in the different points of network. In this paper, an adaptive method is proposed based on available setting groups (SG) of relays. Since the number of available SG is less than possible CADD states, a classifying index (CI) is defined to categorize the several states in restricted setting groups. Genetic algorithm (GA) with a suitable objective function (OF) is used as an optimization method for the classification. After grouping, a modified coordination method is applied to achieve optimal coordination for each group. The efficiency of the proposed technique is demonstrated by simulation results.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.6 no.4
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• pp.243-248
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• 2013

In this thesis, we have designed the indirect adaptive controller using Dynamic Neural Units(DNU) for unknown nonlinear systems. Proposed indirect adaptive controller using Dynamic Neural Unit based upon the topology of a reverberating circuit in a neuronal pool of the central nervous system. In this thesis, we present a genetic DNU-control scheme for unknown nonlinear systems. Our method is different from those using supervised learning algorithms, such as the backpropagation (BP) algorithm, that needs training information in each step. The contributions of this thesis are the new approach to constructing neural network architecture and its training.

• BMB Reports
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• v.46 no.11
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• pp.519-526
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• 2013

Dopamine (DA) regulates emotional and motivational behavior through the mesolimbic dopaminergic pathway. Changes in DA signaling in mesolimbic neurotransmission are widely believed to modify reward-related behaviors and are therefore closely associated with drug addiction. Recent evidence now suggests that as with drug addiction, obesity with compulsive eating behaviors involves reward circuitry of the brain, particularly the circuitry involving dopaminergic neural substrates. Increasing amounts of data from human imaging studies, together with genetic analysis, have demonstrated that obese people and drug addicts tend to show altered expression of DA D2 receptors in specific brain areas, and that similar brain areas are activated by food-related and drug-related cues. This review focuses on the functions of the DA system, with specific focus on the physiological interpretation and the role of DA D2 receptor signaling in food addiction.