• 한국지능시스템학회논문지
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• 제14권4호
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• pp.445-450
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• 2004

본 논문은 실질적인 최적화 구조물의 설계를 위한 시스템에 대한 것으로 퍼지이론에 바탕을 둔 자동 유한요소 생성 망 기술과 계산 기하학적 기술, 해석코드 및 솔리드모델러를 시스템에 통합시켰다. 최적해 또는 만족해는 자동해석 시스템과 함께 탐색공간을 위한 유전자 알고리즘을 이용하여 자동적으로 탐색되어 진다. 또한, 유전자 알고리즘을 이용함으로써 본 설계 시스템은 다차원 해를 얻을 수 있다. 개발된 시스템은 터널전류에 바탕을 둔 마이크로 가속도계의 형상설계에 적용하였다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2002년도 하계학술대회 논문집 A
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• pp.87-89
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• 2002

This paper presents a new approach using an Improved branch exchange (IBE) technique to maximize the voltage stability as well as loss minimization in radial power systems. A suitable voltage stability index (VSI) for optimal routing algorithm is developed using novel methods both a critical transmission path based on a voltage phasor approach and an equivalent impedance method. Furthermore, the proposed algorithm can automatically detect the critical transmission path to be reached to a critical load faced with voltage collapse due to additional real or reactive leading. To develop an effective optimization technique, we also have applied a branch exchange algorithm based on a newly derived index of loss change. The proposed IBE algorithm for VSI maximization can effectively search the optimal topological structures of distribution feeders by changing the open/closed states of the sectionalizing and tie switches. The proposed algorithm has been tested with the various radial power systems to show its favorable performance.

• International journal of advanced smart convergence
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• 제9권1호
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• pp.132-140
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• 2020

It is very important to use appropriate nutrition water for crop growth in hydroponic farming facilities. However, in many cases, the supply of nutrition water is not designed with a precise plan, but is performed in a conventional manner. We proposes a forecasting technique for nutrition water requirements based on a data analysis for optimal strawberry production. To do this, the proposed forecasting technique uses linear regression for correlating strawberry production, soil condition, and environmental parameters with nutrition water demand for the actual two-stage strawberry production soil. Also, it includes predicting the optimal amount of nutrition water requires according to the heterogeneous cultivation environment and variety by comparing the amount of nutrition water needed for the growth and production of different kinds of strawberries. We suggested study uses two types of section beds that are compared to find out the best section bed production of strawberry growth. The dataset includes 233 samples collected from a real strawberry greenhouse, and the four predicted variables consist of the total amounts of nutrition water, average temperature, humidity, and CO₂ in the greenhouse.

• 전자공학회논문지B
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• 제32B권5호
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• pp.77-86
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• 1995

In this paper in order to reduce the encoding complexity required in the full search vector quantization(VQ), a new classified vector quantization(CVQ) technique is described employing the minimum-distance classifier. The determination of the optimal subcodebook sizes for each class is an important task in CVQ designs and is not an easy work. Therefore letting the subcodebook sizes be equal. A CVQ technique. Which satisties the optimal CVQ condition approximately, is proposed. The proposed CVQ is a kind of the partial search VQ because it requires a search process within each subcodebook only, and the minimum encoding complexity since the subcodebook sizes are the same in each class. But simulation results reveal while the encoding complexity is only O(N$^{1/2}$) comparing with O(N) of the full-search VQ. A simple systolic array, which has the through-put of k, is also proposed for the implementation of the VQ. Since the operation of the classifier is identical with that of the VQ, the proposed array is applied to both the classifier and the VQ in the proposed CVQ, which shows the usefulness of the proposed CVQ.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 2003년도 봄 학술발표회 논문집
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• pp.288-295
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• 2003

An adaptive procedure in finite element analysis is presented by p-refinement of meshes in conjunction with a posteriori error estimator that is based on the recovery technique. In case of the recovery technique, the SPR(superconvergent patch recovery) approach has been modified for p-adaptive mesh refinement. The strategy of finding a nearly optimal distribution of polynomial degrees on a fixed finite element mesh is discussed such that a particular element has to be refined automatically to obtain an acceptable level of accuracy by increasing p-levels non-uniformly. To verify the proposed algorithm, the limit value approach is proposed which utilizes the exact strain energy computed from the extrapolation equation. A new pre-processor is developed for the p-version finite element program in which the vector graphic editor is used for the automatic generation of node connection and coordinate by halfedge solid data structure according to uniform or nonuniform p-distribution. The general 2-D algorithm is also developed to generate face modes and internal modes in accordance with different mesh types. The quality of the error estimator is investigated with the help of two mumerical examples. The results show that the sequences of p-distributions obtained by the proposed error indicator closely follow the optimal trajectory.

• 한국철도학회:학술대회논문집
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• 한국철도학회 2007년도 추계학술대회 논문집
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• pp.158-166
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• 2007

한국철도공사는 고속철도의 운행을 계기로 선진철도 정비방법의 습득과 더불어 기존차량에 대한 검수주기 및 방법에 대한 과학적이고 체계적인 시행을 위해 철도차량 RCM적용에 관한 연구를 시행 중이다. 그 동안 철도차량의 부품과 시스템에 대한 기술의 발전이 급속히 이루어지고 있는 것에 비해 정비방법의 발전은 상대적으로 느렸다고 할 수 있다. 이에 한국철도공사에서는 부품과 시스템의 기술발전에 앞서는 정비방법의 적용은 물론이고 차량의 기술적 발전을 리드할 수 있는 정비체계를 구축하고자 노력하고 있다. 고속차량인 KTX를 제외한 기존차량은 전동차, 전기기관차, 디젤기관차, 디젤동차, 객차, 화차 등으로 구분하여 운행되고 있다. 그 중 객차, 화차를 포함한 기존차종에 현행 시행되고 있는 검수 주기 및 방법을 분석하여 개선방향을 찾아 최적의 차량정비 주기 및 방법을 적용하고자 한다.

• 산업경영시스템학회지
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• 제39권1호
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• pp.105-115
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• 2016

Ensemble classification involves combining individually trained classifiers to yield more accurate prediction, compared with individual models. Ensemble techniques are very useful for improving the generalization ability of classifiers. The random subspace ensemble technique is a simple but effective method for constructing ensemble classifiers; it involves randomly drawing some of the features from each classifier in the ensemble. The instance selection technique involves selecting critical instances while deleting and removing irrelevant and noisy instances from the original dataset. The instance selection and random subspace methods are both well known in the field of data mining and have proven to be very effective in many applications. However, few studies have focused on integrating the instance selection and random subspace methods. Therefore, this study proposed a new hybrid ensemble model that integrates instance selection and random subspace techniques using genetic algorithms (GAs) to improve the performance of a random subspace ensemble model. GAs are used to select optimal (or near optimal) instances, which are used as input data for the random subspace ensemble model. The proposed model was applied to both Kaggle credit data and corporate credit data, and the results were compared with those of other models to investigate performance in terms of classification accuracy, levels of diversity, and average classification rates of base classifiers in the ensemble. The experimental results demonstrated that the proposed model outperformed other models including the single model, the instance selection model, and the original random subspace ensemble model.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2012년도 춘계학술대회 논문집
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• pp.361-366
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• 2012

In this paper, we propose the efficient technique that reduces the number of spot-welds and increases the structural rigidity by using the topology optimization technique. Eigen value analysis is used to evaluate the rigidity of the optimized model. As a first step, the topology optimization is performed to find optimal spot-weld distributions. In this study, the design objective is to maximize the weighted frequencies. The volume fractions of the weld components are used as design constraints, and also the densities of each element in the individual design space are used as design variables. And then, to consider the possibility of spot-weld failure, the contribution rate analysis was performed by using the orthogonal array method of DOE. The spot-welds in the rear panel part are reinforced according to estimation results of the contribution rate analysis. Finally, we obtained optimized spot-weld layout model which has the reduced number of spot-welds and the improved dynamic stiffness.

• 한국전산유체공학회지
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• 제11권1호
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• pp.57-66
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• 2006

An optimal shape design approach is presented for a subsonic S-shaped intake using aerodynamic sensitivity analysis. Two-equation turbulence model is employed to capture strong counter vortices in the S-shaped duct more precisely. Sensitivity analysis is performed for the three-dimensional Navier-Stokes equations coupled with two-equation turbulence models using a discrete adjoint method For code validation, the result of the flow solver is compared with experiment data and other computational results of bench marking test. To study the influence oj turbulence models and grid refinement on the duct flow analysis, the results from several turbulence models are compared with one another and the minimum number of grid points, which can yield an accurate solution is investigated The adjoint variable code is validated by comparing the complex step derivative results. To realize a sufficient and flexible design space, NURBS equations are introduced as a geometric representation and a new grid modification technique, Least Square NURBS Grid Approximation is applied With the verified flow solver, the sensitivity analysis code and the geometric modification technique, the optimization of S-shaped intake is carried out and the enhancement of overall intake performance is achieved The designed S-shaped duct is tested in several off-design conditions to confirm the robustness of the current design approach. As a result, the capability and the efficiency of the present design tools are successfully demonstrated in three-dimensional highly turbulent internal flow design and off-design conditions.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제4권2호
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• pp.135-141
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• 2004

This paper proposes a new heuristic search technique for obstacle avoidance of autonomous underwater vehicles equipped with a looking ahead obstacle avoidance sonar. We suggest the fuzzy relation between the sonar sections and the properties of real world environment. Bandler and Kohout's fuzzy relational method are used as the mathematical implementation for the analysis and synthesis of relations between the partitioned sections of sonar over the real-world environmental properties. The direction of the section with optimal characteristics would be selected as the successive heading of AUVs for obstacle avoidance. For the technique using in this paper, sonar range must be partitioned into multi equal sections; membership functions of the properties and the corresponding fuzzy rule bases are estimated heuristically. With the two properties Safety, Remoteness and sonar range partitioned in seven sections, this study gives the good result that enables AUVs to navigate through obstacles in the optimal way to goal.