• The Journal of Information Systems
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• v.3
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• pp.147-169
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• 1994

This paper present s a pattern generation scheme from financial charts. The patterns constitute knowledge which consists of patterns as the conditional part and the impact of the pattern as the conclusion part. The patterns in charts are represented in a syntactic approach. If the pattern elements and the impact of patterns are defined, the patterns are synthesized from simple to the more highly credible by evaluating each intermediate pattern from the instances. The overall process is divided into primitive discovery by Genetic Algorithms and pattern synthesis from the discovered primitives by the Syntactic Pattern-based Inductive Learning (SYNPLE) algorithm which we have developed. We have applied the scheme to a chart : the trend lines of stock price in daily base. The scheme can generate very credible patterns from training data sets.

• Journal of Mechanical Science and Technology
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• v.17 no.7
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• pp.966-977
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• 2003

This paper investigates how intentional mistuning of bladed disks reduces their sensitivity to unintentional random mistuning. The class of intentionally mistuned disks considered here is limited, for cost reasons, to arrangements of two types of blades (A and B, say). A two-step procedure is then described to optimize the arrangement of these blades around the disk to reduce the effects of unintentional random mistuning. First, a pure optimization effort is undertaken to obtain the pattern (s) of the A and B blades that yields small/the smallest value of the largest amplitude of response to a given excitation in the absence of unintentional random mistuning using Genetic Algorithm. Then, in the second step, a qualitative/quantitative estimate of the sensitivity for the optimized intentionally mistuned bladed disks with respect to unintentional random mistuning is performed by analyzing their amplification factor, probability density function and passband/stopband structures. Examples of application with simple bladed disk models demonstrate the significant benefits of using this class of intentionally mistuned disks.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.10a
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• pp.1076-1079
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• 1997

A new 3D micromachining method, called Hole Area Modulation(HAM), has been introduced and experimentally confirmed its feasibility. In this method, information on the depth of machining is converted to the sizes of small holes in the mask. The machining is carried out with a simple 2D movement of the workpiece. This method can be applied for machining various kinds of microcavities in various materials. In this paper, a mathematical model for excimer laser micromachining based on HAM and also determination of the optimal laser ablation conditions(width, Hole radius, step size, path, etc.) is completed by employing using Genetic Algorithm(GA).

• Journal of Korean Institute of Industrial Engineers
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• v.40 no.3
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• pp.305-312
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• 2014

This research deals with a problem that minimizes makespan in a non-identical parallel machine system with sequence and machine dependent setup times and machine dependent processing times. We first present a new mixed integer programming formulation for the problem, and using this formulation, one can easily find optimal solutions for small problems. However, since the problem is NP-hard and the size of a real problem is large, we propose four heuristic algorithms including genetic algorithm based heuristics to solve the practical big-size problems in a reasonable computational time. To assess the performance of the algorithms, we conduct a computational experiment, from which we found the heuristic algorithms show different performances as the problem characteristics are changed and the simple heuristics show better performances than genetic algorithm based heuristics for the case when the numbers of jobs and/or machines are large.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.2
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• pp.95-100
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• 2001

비선형 시스템의 성공적인 퍼지 모델을 구성하기 위한 최적의 퍼지 추론 시스템의 동정은 중요하고도 어려운 문제이다. 전통적으로 유전 알고리즘은 어느 정도의 전역 최적해를 찾을 수 있기 때문에 퍼지 모델의 구조와 파라미터를 동정하는데 사용되어 왔다. 그러나, 유전 알고리즘은 개체군 진화 시 우수한 개체의 출현은 지역수렴의 원인이 된다. 따라서, 본 논문에서는 바이러스 메시 유전알고리즘을 이용한 효과적인 퍼지 모델링 방법을 제안한다. 제안된 방법은 지역 정보가 개체군 내에서 교환됨으로써 지역 수렴의 대인아 될 수 있을 뿐 아니라, 가변길이 스트링을 사용함으로써 좀더 효과적이고 적응적인 구조를 가질 수 있다. 또한 본 논문에서 제안한 방법의 우수성과 일반성을 증명하기 위해 복잡한 비선형 시스템과 가스로의 퍼지모델링에 적용하였다.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.234-234
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• 2000

A direct torque control(DTC) based sensorless speed control system which employs a new closed loop flux observer is proposed. The flux observer takes an adaptive scheduling gains where motet speed is used as the scheduling variable. Adaptive nature comes from the fact that the estimated values of stator resistance and speed are included as observer parameters. The parameters of the PI controllers adopted in the adaptive law for the estimation of stator resistance and motor speed are determined by simple genetic algorithm. Simulation results in low speed region are given for comparison between proposed and conventional flux estimate scheme.

• CDE review
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• v.21 no.2
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• pp.31-33
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• 2015

This paper deals with synthesis of 4 bar linkage by using optimum design. To design 4 bar linkage, overlay method is proposed and for optimization, genetic algorithm is applied with objective function. The accuracy of this method will be determined by errors between real value and test value. We will use Chebychev spacing to get 3 precision positions of input angles. The output angles will be determined by the function that the designer wants input and output relations to be. It will be applied to example to show the accuracy of this method. The advantages of using this method are that it is fast to get optimal solution and it is simple to use.

• Proceedings of the IEEK Conference
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• 2002.07c
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• pp.1650-1653
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• 2002

In this paper, we propose the initial optimized structure of the Radial Basis function Networks that is simple in the part of the structure and fast converges more than neural networks with the analysis method using Time- Frequency Localization. We construct the hidden node with the Radial Basis functions their localization are similar with approximation target function in the plane of the Time and Frequency. We finally make a good decision of the initial structure for function approximation using genetic algorithm

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.8
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• pp.623-631
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• 2003

We have fabricated the two-dimensional inverted pendulum system and designed its controller. The two-dimensional inverted pendulum system, which is composed of X-Y table, is actuated through timing belt by each of two geared DC motors. And the control goal is that the rod is always kept to a vertical position to any distrubance and is quickly moved to the desired position. Because this system has generally nonlinear dynamic characteristics and X-axis and Y-axis move together, it is very difficult to find its exact mathematical model and to design its controller. Therefore, we have designed the PID controller with simple structure and excellent performance. Genetic algorithm(GA), which is blown as one of probabilistic searching methods, and human's heuristic control strategy are introduced to design an optimal PID controller. The usefulness of the proposed GA based PID coefficient searching technique is verified through the experiments and computer simulations.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.23 no.1
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• pp.56-61
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• 2015

Because of kinematic complexities, nonlinear behavior, etc, the performance of oleo-pneumatic landing gear is predicted by qualified commercial softwares. While commercial softwares predict more exactly, it takes a long time to construct or modify a model. At initial design stage, design parameters can be determined quickly and exactly enough with simple 2 degree of freedom model of mass, spring and damping. 2 degree of freedom model can be easily applied to optimization and reliability analysis which takes repetitive computation. In this paper, oleo-pneumatic landing gear is modeled as a nonlinear 2 degree of freedom model. The analysis are compared with landing gear drop test. To determine design parameter, optimization problem is solved with genetic algorithm and 2 degree of freedom model.