• Journal of the Korea Institute of Information and Communication Engineering
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• v.5 no.3
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• pp.543-551
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• 2001

This paper is concerned with optimization of a motor torque to drive Parking Sign system. It needs to minimize powers for stand alone operation and requires the optimized parameters in order to move the plates in the minimum torque. The operation can be represented as a complicated non-linear equation which is difficult to solve by general optimization techniques. In this paper, the dynamic equations of the system are derived, also the suitable Genetic Algorithm is designed to solve the equations. Computer simulation shows the availability of this method.

• Journal of the Korea Concrete Institute
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• v.20 no.6
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• pp.705-712
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• 2008

This study carried out simulation for structural layout design for concrete structures by using the models of the ground structure method. The micro lattice truss is modeled as assemblage of a number of unit cells. The progress of analysis repeat to undergo finite element analysis to feed-back results of stress to the stiffness of each member. Through the repeated this analysis, truss model is represented to form the topological materials and the structural shape with the use of the local stress condition without mathematical optimum tools. It is successful to analyse the shape-layout problem as numerical samples on the lattice truss model.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.5
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• pp.557-562
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• 2004

This paper deals with a robust mixed ${H_2}/{H_{\infty}}$ filter design problem for a nonlinear dynamic system modeled as a T-S fuzzy system. Integral quadratic constraints are used to describe various kinds of uncertainties of the plant. A sufficient condition for solvability is given in terms of linear matrix inequality problem which can be efficiently solved using a convex optimization technique. In order to demonstrate the Proposed method, a numerical design example is provided.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.5 no.3
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• pp.49-59
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• 1985

Formulation of the geometric optimization for truss structures based on the elasticity theory turn out to be the nonlinear programming problem which has to deal with the Cross sectional area of the member and the coordinates of its nodes simultaneously. A few techniques have been proposed and adopted for the analysis of this nonlinear programming problem for the time being. These techniques, however, bear some limitations on truss shapes loading conditions and design criteria for the practical application to real structures. A generalized algorithm for the geometric optimization of the truss structures which can eliminate the above mentioned limitations, is developed in this study. The algorithm developed utilizes the two-phases technique. In the first phase, the cross sectional area of the truss member is optimized by transforming the nonlinear problem into SUMT, and solving SUMT utilizing the modified Newton-Raphson method. In the second phase, the geometric shape is optimized utilizing the unidirctional search technique of the Rosenbrock method which make it possible to minimize only the objective function. The algorithm developed in this study is numerically tested for several truss structures with various shapes, loading conditions and design criteria, and compared with the results of the other algorithms to examme its applicability and stability. The numerical comparisons show that the two-phases algorithm developed in this study is safely applicable to any design criteria, and the convergency rate is very fast and stable compared with other iteration methods for the geometric optimization of truss structures.

• Journal of Korea Society of Industrial Information Systems
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• v.27 no.2
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• pp.61-69
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• 2022

A multi-agent system is a system that aims at achieving the best-coordinated decision based on each agent's local decision. In this paper, we consider a multi agent-multi task assignment problem. Each agent is assigned to only one task and there is a completion probability for performing. The objective is to determine an assignment that maximizes the sum of the completion probabilities for all tasks. The problem, expressed as a non-linear objective function and combinatorial optimization, is NP-hard. It is necessary to design an effective and efficient solution methodology. This paper presents an approximation algorithm using submodularity, which means a marginal gain diminishing, and demonstrates the scalability and robustness of the algorithm in theoretical and experimental ways.

• Journal of Korean Society of Steel Construction
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• v.12 no.3 s.46
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• pp.317-328
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• 2000

The objective of the research is to develop an algorithm for the optimum design of two-dimensional braced steel frames using an advanced analysis, which considers both material and geometric nonlinearties. Since both nonlinearties are considered in analysis process, Optimum design algorithm which does not require to calculate K-factor is presented. A multi-level discrete optimization technique with two parameters that uses the information of structural system and separate member has been developed. The structural analysis is performed by the relined plastic-hinge method which is based on zero-length plastic hinge theory. Optimization problem are formulated by AISC-LRFD code. The feasibility, validity and efficiency of the developed algorithm is demonstrated by the results of the braced steel frame.

• The Korean Journal of Applied Statistics
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• v.11 no.2
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• pp.451-459
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• 1998

The analysis of data from a multiresponse experiment requires careful consideration of the multivariate nature of the data. In a multiresponse sitation, the optimization problem is more complex than in the single response case. The biplot is a graphical tool which make the analyst to understand the correlation of the response variables, the relation of the response variables arid the explanatory variables and the relative importance of the explanatory variables. In case of good fitting of the first order model, we can draw the biplot with the first order experimental design. Otherwise, we can make the biplot with the second order experimental design by adding other experimental points.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2006.11a
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• pp.366-369
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• 2006

본 논문에서는 계층적 공정 경쟁 유전자 알고리즘을 통한 비선형시스템의 정보입자 기반 퍼지집합 퍼지집합 모델의 최적화 방법을 제안한다. 퍼지집합 모델은 주로 전문가의 경험에 기반을 두어 얻어지기 때문에 동정과 최적화 과정이 필요하며 GAs를 이용하여 퍼지모델을 최적화한 연구가 많이 있다. GAs는 전역 해를 찾을 수 있는 최적화 알고리즘으로 잘 알려져 있지만 조기 수렴 문제를 포함하고 있다. 병렬유전자 알고리즘(PGA)은 조기수렴를 더디게 하고 전역 해를 찾기 위한 진화알고리즘이다. 적응형 계층적 공정 경쟁기반 유전자 알고리즘(AHFCGA)을 이용하여 퍼지모델의 입력변수, 멤버쉽함수의 수, 멤버쉽함수의 정점 등의 전반부 구조와 파라미터를 동정하였고, LSE를 사용하여 후반부 파라미터를 동정하였으며 실험적 예제를 통하여 제안된 방법의 성능을 평가한다.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.8
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• pp.720-725
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• 2001

Derivation of TSK fuzzy model from nonlinear differential equation is fundamental issue in the field of theoretical fuzzy control. The method which does not yield affine local differential equations at off-equilibrium points is proposed in this paper. A prototype TSK fuzzy model which has triangular membership functions for linguistic terms of the antecedent part is derived systematically. And then GA is used to modify the membership functions optimally. Simulation results show the validity of the proposed method.

• Journal of the Korean Data and Information Science Society
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• v.21 no.2
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• pp.211-218
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• 2010

Taguchi has used the signal-to-noise ratio (SN) to achieve the appropriate set of operating conditions where variability around target is low in the Taguchi parameter design. Many Statisticians criticize the Taguchi techniques of analysis, particularly those based on the SN. Moreover, there are difficulties in practical application, such as complexity and nonlinear relationships among quality characteristics and design (control) factors, and interactions occurred among control factors. Neural networks have a learning capability and model free characteristics. There characteristics support neural networks as a competitive tool in processing multivariable input-output implementation. In this paper we propose a substantially simpler optimization procedure for parameter design using neural network without resorting to SN. An example is illustrated to compare the difference between the Taguchi method and neural network method.