• The Transactions of the Korean Institute of Electrical Engineers P
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• v.64 no.3
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• pp.169-174
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• 2015

Noise problem that occurs on the road is raising a lot of problems in the economic, social and environmental aspects. The active noise control (ANC) systems based on the filtered-X least mean square(FxLMS) algorithm have a problem with compensating the acoustic feedback of secondary route. However, newly proposed correlation-LMS(CLMS) and expanded CLMS algorithms have slightly much calculation and are minutely behind performance, these have a advantage not in measuring transfer function onerously so that we can easily adapt these in real time. The CLMS and expanded CLMS algorithm was developed to improve the real-time implementation performance under the variable input noise such as road noise environment. In this paper, we compared and analyzed their performance. From the results of the Matlab simulation for an ANC system, it is shown that expanded CLMS algorithms are more convergence speed and keep the desirable performance even in the input of road noise situation.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.18 no.4
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• pp.30-37
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• 2010

This paper deals with attitude determination and parameter estimation problems for a lunar module. For this we first derive equations of motion for the lunar module by considering allocation locations (configurations) of reaction thruster and a reaction wheel assembly. The lunar module is assumed as a rigid body. In order to include the effect of fuel sloshing on the dynamics of the lunar module, we model it as a spherical pendulum for a simple analysis. For estimating angular rates and moment of inertia of the module, we employ an extended Kalman filter and the least mean square algorithms, respectively. Finally we construct a dynamical model for the lunar module by combining all these elements.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.4
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• pp.505-510
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• 2005

The RPO(randomized policy optimizer) algorithm, which utilizes probabilistic policy for the action selection, is a recently developed tool in the area of reinforcement learning, and has been shown to be very successful in several application problems. In this paper, we propose a modified RPO algorithm, whose critic network is adapted via RLS(Recursive Least Square) algorithm. In order to illustrate the applicability of the modified RPO method, we applied the modified algorithm to Kimura's robot and observed very good performance. We also developed a MATLAB-based animation program, by which the effectiveness of the training algorithms on the acceleration or the robot movement were observed.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.8
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• pp.754-759
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• 2001

In this paper, we propose a TSK(Takagi-Sugeno-Kang)-type fuzzy classifier using PCA(Principal Component Analysis), FCM(Fuzzy c-Means) clustering, ANFIS(Adaptive Neuro-Fuzzy Inference System) and hybrid GA(Genetic Algorithm). First, input data is transformed to reduce correlation among the data components by PCA. FCM clustering is applied to obtain a initial TSK-type fuzzy classifier. Parameter identification is performed by AGA(Adaptive GA) and RLSE(Recursive Least Square Estimate). Finally, we applied the proposed method to Iris data classificationl problems and obtained a better performance than previous works.

• Journal of Convergence Society for SMB
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• v.3 no.2
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• pp.19-25
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• 2013

Decision procedure was done with the evaluation of multi-criterion analysis. Importance of each criterion was considered through heuristically method, specially it was based on the heuristic least mean square algorithm. To consider coalition evaluation, it was carried out by calculation of Shapley index and Interaction value. The model output is also analyzed with the help of those two indexes, and the procedure was also displayed with details. Finally, the differences between the model output and the desired results are evaluated thoroughly, several problems are raised at the end of the example which require for further studying.

• Transactions of the Korean hydrogen and new energy society
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• v.27 no.1
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• pp.36-41
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• 2016

The development need of new renewable energy is more and more important to resolve exhaustion of chemical fuels and environmental pollution. Polymer electrolyte membrane fuel cell has been widely studied to the extent that it can be used commercially. But there are many problems to be solved. One of them is to enhance the stability of fuel cell stacks. This paper proposes a new fault diagnosis method using Least Square Method (LSM) which is one of parameter estimation methods. The proposed method extracts equivalent circuit parameters from on-line measurements. Parameters of the circuit are estimated according to normal and abnormal states using simulation. The variation of parameters estimated in each states enables the estimation of state in fuel cells. Thus the LSM presented can be a suitable on-line parameter estimation method in PEMFC.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.23 no.11
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• pp.943-950
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• 2013

This paper discusses a harmonic response estimation method on the L$\acute{e}$vy plate with two opposite edges simply supported and the other two edges having free boundary conditions. Since the equation of motion of the plate is not self-adjoint, the modes are not orthogonal to each other on the domain. Noting that the L$\acute{e}$vy plate can be expressed using one term sinusoidal function that is orthogonal to other sinusoidal functions, this paper suggested the calculation method that is equivalent to finding a least square error minimization solution of the finite number of algebraic equations. Example problems subjected to a distributed area loading and a distributed line loading are defined and their solutions are provided. The solutions are compared to those of the commercial code, ANSYS. According to the verification results, it is expected that the suggested method will be useful to predict the forced response on the L$\acute{e}$vy plate with the distributed area or line loading conditions.

• Journal of the Korea Society of Computer and Information
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• v.25 no.3
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• pp.109-115
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• 2020

In this paper, we propose an artificial intelligence(AI) technology analysis using partial least square(PLS) regression model. AI technology is now affecting most areas of our society. So, it is necessary to understand this technology. To analyze the AI technology, we collect the patent documents related to AI from the patent databases in the world. We extract AI technology keywords from the patent documents by text mining techniques. In addition, we analyze the AI keyword data by PLS regression model. This regression model is based on the technique of partial least squares used in the advanced analyses such as bioinformatics, social science, and engineering. To show the performance of our proposed method, we make experiments using AI patent documents, and we illustrate how our research can be applied to real problems. This paper is applicable not only to AI technology but also to other technological fields. This also contributes to understanding other various technologies by PLS regression analysis.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.10 s.181
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• pp.2469-2476
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• 2000

The meshing of the domain has long been the major bottleneck in performing the finite element analysis. Research efforts which are so-called meshfree methods have recently been directed towards eliminating or at least easing the requirement for meshing of the domain. In this paper, a new meshfree method for solving nonlinear boundary value problem, based on the bubble packing technique and Delaunay triangle is proposed. The method can be efficiently implemented to the problems with singularity by using formly distributed nodes.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2003.05a
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• pp.430-433
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• 2003

This paper presents a system identification (SI) scheme in time domain using measured acceleration data. The error function is defined as the time integral of the least square errors between the measured acceleration and the calculated acceleration by a mathematical model. Damping parameters as well as stiffness properties of a structure are considered as system parameters. The structural damping is modeled by the Rayleigh damping in SI. The regularization technique is applied to alleviate the ill-posed characteristics of inverse problems. The validity of the proposed method is demonstrated by an experimental study on a shear building model.