• Transactions of the Korean Society of Mechanical Engineers
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• v.12 no.4
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• pp.730-737
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• 1988

Determining the robot motion using optimal technique has been studied often in recent years however the study of determining the optimal robot dimensions is very rare. In this paper, the authors attempted to find out the least driving torques at each joint as the optimization of link length refered to a 3R robot manipulator. For the given linear path with triangular velocity profile, the inverse kinematic and inverse dynamic problems are examined in order to lead into solution of problem suggested for optimal design of link lengths. Accordingly, optimal link lengths in the case of given linear path is obtained with respect to the parameter of link ratios.

• Proceedings of the KIEE Conference
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• 1996.07a
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• pp.154-156
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• 1996

A new method for electric resistivity tomography(ERT) is developed for geophysical inverse problems by adapting the sensitivity analysis. The outputs of the potential electrodes are computed using two dimensional finite element method in the wave number space by Fourier transforming the governing equations. The resistance distribution in the region of interests, which makes the computed potential distribution coincide with the measured potential, is found by minimizing the objective function using an optimization method. In this process the sensitivity analysis is introduced in order to compute the derivatives of the objective function. And an adjoint variable method is used to save the computational efforts for sensitivity coefficients.

• Proceedings of the KIEE Conference
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• 2006.10c
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• pp.220-222
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• 2006

This paper presents intelligent digital redesign method of global approach for hybrid state space fuzzy-model-based controllers. For effectiveness and stabilization of continuous-time uncertain nonlinear systems under discrete-time controller, Takagi-Sugeno(TS) fuzzy model is used to represent the complex system. And global approach design problems viewed as a convex optimization problem that we minimize the error of the norm bounds between nonlinearly interpolated lineal operators to be matched. Also, by using the bilinear and inverse bilinear approximation method, we analyzed nonlinear system's uncertain parts more precisely. When a sampling period is sufficiently small, the conversion of a continuous-time structured uncertain nonlinear system to an equivalent discrete-time system have proper reason. Sufficiently conditions for the global state-matching of the digitally controlled system are formulated in terms of linear matrix inequalities (LMIs). Finally, a T-S fuzzy model for the chaotic Lorentz system is used as an example to guarantee the stability and effectiveness of the proposed method.

• Journal of Mechanical Science and Technology
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• v.16 no.4
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• pp.454-467
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• 2002

It has been established that a crack has an important effect on the dynamic behavior of a structure. This effect depends mainly on the location and depth of the crack. Toidentifythelocation and depth of a crack in a structure, a method is presented in this paper which uses neuro-fuzzy-evolutionary technique, that is, Adaptive-Network-based Fuzzy Inference System (ANFIS) solved via hybrid learning algorithm (the back-propagation gradient descent and the least-squares method) and Continuous Evolutionary Algorithms (CEAs) solving sir ale objective optimization problems with a continuous function and continuous search space efficiently are unified. With this ANFIS and CEAs, it is possible to formulate the inverse problem. ANFIS is used to obtain the input(the location and depth of a crack) - output(the structural Eigenfrequencies) relation of the structural system. CEAs are used to identify the crack location and depth by minimizing the difference from the measured frequencies. We have tried this new idea on beam structures and the results are promising.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.11a
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• pp.743-747
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• 1996

A Potential Field Method is applied to the proposed algorithm for the planning of collision-free paths of redundant manipulators. The planning is carried out on the base of kinematic configuration. To make repulsive potentials, sources are distributed on the boundaries of obstacles. To escape from local minimum of the main potential and to attack other difficulties of the planning, various potentials are defined simultaneously, Inverse Kinematics Problems of the redundant manipulators are solved by unconstrained optimization method. Computer simulation result of the path planning is presented.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1998.04a
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• pp.101-109
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• 1998

Genetic Algorithm(GA), which is based on the theory of natural evolution, has been evaluated highly for their robust performances. The optimization problems on truss structures under the prescribed displacement are solved by using GA. In this paper, the homologous deformation of structures was proposed as the prescribed displacement. The shape analysis of structures is a kind of inverse problems different from stress analysis, and the governing equation becomes nonlinear. In this regard, GA was used to solve the nonlinear equation. In this study, the shape analysis method in which not only the positions of the objective nodes but also the layout and sectional area of the member are encoded to strings in the GA as design parameters of the structures is proposed.

• Journal of the Korea Society of Computer and Information
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• v.24 no.10
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• pp.57-64
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• 2019

In this paper, we study a polynomially solvable case of the inverse interval graph coloring problem. Given an interval graph associated with a specific interval system, the inverse interval graph coloring problem is defined with the assumption that there is no proper K-coloring for the given interval graph, where K is a fixed integer. The problem is to modify the system of intervals associated with the given interval graph by shifting some of the intervals in such a way that the resulting interval graph becomes K-colorable and the total modification is minimum with respect to a certain norm. In this paper, we focus on the case K = 1 where all intervals associated with the interval graph have length 1 or 2, and interval displacement is only allowed to the righthand side with respect to its original position. To solve this problem in polynomial time, we propose a two-phase algorithm which consists of the sorting and First Fit procedure.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.6
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• pp.807-812
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• 2007

Recently, Extreme learning machine(ELM), a novel learning algorithm which is much faster than conventional gradient-based learning algorithm, was proposed for single-hidden-layer feedforward neural networks. The initial input weights and hidden biases of ELM are usually randomly chosen, and the output weights are analytically determined by using Moore-Penrose(MP) generalized inverse. But it has the difficulties to choose initial input weights and hidden biases. In this paper, an advanced method using the bacterial foraging algorithm to adjust the input weights and hidden biases is proposed. Experiment at results show that this method can achieve better performance for problems having higher dimension than others.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.25 no.12
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• pp.2062-2069
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• 2001

It has been established that a crack has an important effect on the dynamic behavior of a structure. This effect depends mainly on the location and depth of the crack. To identify the location and depth of a crack in a structure, a method is presented in this paper which uses synthetic artificial intelligent technique, that is, Adaptive-Network-based Fuzzy Inference System(ANFIS) solved via hybrid learning algorithm(the back-propagation gradient descent and the least-squares method) are used to learn the input(the location and depth of a crack)-output(the structural eigenfrequencies) relation of the structural system. With this ANFIS and a continuous evolutionary algorithm(CEA), it is possible to formulate the inverse problem. CEAs based on genetic algorithms work efficiently for continuous search space optimization problems like a parameter identification problem. With this ANFIS, CEAs are used to identify the crack location and depth minimizing the difference from the measured frequencies. We have tried this new idea on a simple beam structure and the results are promising.

• Proceedings of the KSME Conference
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• 2001.06c
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• pp.182-188
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• 2001

It has been established that a crack has an important effect on the dynamic behavior of a structure. This effect depends mainly on the location and depth of the crack. To identify the location and depth of a crack in a structure, a method is presented in this paper which uses synthetic artificial intelligent technique, that is, Adaptive-Network-based Fuzzy Inference System(ANFIS) solved via hybrid learning algorithm(the back-propagation gradient descent and the least-squares method) are used to learn the input(the location and depth of a crack)-output(the structural eigenfrequencies) relation of the structural system. With this ANFIS and a continuous evolutionary algorithm(CEA), it is possible to formulate the inverse problem. CEAs based on genetic algorithms work efficiently for continuous search space optimization problems like a parameter identification problem. With this ANFIS, CEAs are used to identify the crack location and depth minimizing the difference from the measured frequencies. We have tried this new idea on a simple beam structure and the results are promising.