• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1403-1406
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• 1997

Generally, G.P.S(Global Positioning System) is using for the car navigation system but it has some restrictions such as the discontinuity of earth satellites and SA (Selective Availability). Recently, the hybrid navigation system combining with G.P.S and Dead-reckoning are much attractuve for improving the accuracy of a vehicle positioning. G.P.S called satellite navigation system, can measure its position by using satellites. Dead-Reckoning is the self-contained navigatioin system using a wheel sensor for the vehicle velocity and a gyro sensor for the vehicle angular velocity. Some algorithm could be generated for finding the vehicle position and orientation. In this paper, we developed a hybrid algotithm wiht G.P.S DR and Map-Matching.

• Transactions of the Korean Society of Automotive Engineers
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• v.9 no.5
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• pp.122-130
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• 2001

In this paper, an operational algorithm for a 2-shaft parallel hybrid electric vehicle is suggested for the minimization of operation cost. The operation cost is obtained as a summation of the engine fuel cost and the motor electricity cost. The electrical cost function is estimated in case of motoring, and generating when the recuperation is carried out during the braking. In addition, weight function is introduced in order to maintain the battery state of charge. Based on the operation algorithm, the optimal engine operation point that minimizes the operation cost is obtained with respect to the required vehicle power for every state of charge of battery. The optimal operation point provides the optimal power distribution of the engine and the motor for a required vehicle power Simulation was performed and the fuel economy of the hybrid vehicle was compared to that of the conventional vehicle. Simulation results showed that hybrid vehicle's fuel economy can be improved as much as 45∼48% compared to the conventional vehicle's.

• Proceedings of the Korean Statistical Society Conference
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• 2000.11a
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• pp.135-140
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• 2000

베이지안 신경망 모형(Bayesian Neural Networks Models)에서 주어진 입력값(input)은 블랙 박스(Black-Box)와 같은 신경망 구조의 각 층(layer)을 거쳐서 출력값(output)으로 계산된다. 새로운 입력 데이터에 대한 예측값은 사후분포(posterior distribution)의 기대값(mean)에 의해 계산된다. 주어진 사전분포(prior distribution)와 학습데이터에 의한 가능도함수(likelihood functions)를 통해 계산되어진 사후분포는 매우 복잡한 구조를 갖게 됨으로서 기대값의 적분계산에 대한 어려움이 발생한다. 이때 확률적 추정에 의한 근사 방법인 몬테칼로 적분을 이용한다. 이러한 방법으로서 Hybrid Monte Carlo 알고리즘은 우수한 결과를 제공하여준다(Neal 1996). 본 논문에서는 Hybrid Monte Carlo 알고리즘과 기존에 많이 사용되고 있는 Gibbs sampling, Metropolis algorithm, 그리고 Slice Sampling등의 몬테칼로 방법들을 비교한다.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2005.05a
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• pp.960-968
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• 2005

The high cost in maintaining complex manufacturing process makes it necessary to enhance an efficient maintenance system. For the effective maintenance of manufacturing process, precise fault diagnosis should be performed and an appropriate maintenance action should be executed. This paper suggests an intelligent fault diagnosis system using hybrid data mining. In this system, the rules for the fault diagnosis are generated by hybrid decision tree/genetic algorithm and the most effective maintenance action is selected by decision network and AHP. To verify the proposed intelligent fault diagnosis system, we compared the accuracy of the hybrid decision tree/genetic algorithm with one of the general decision tree learning algorithm(C4.5) by data collected from a coil-spring manufacturing process.

• Journal of Information Processing Systems
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• v.13 no.2
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• pp.215-235
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• 2017

Foraging is a biological process, where a bacterium moves to search for nutriments, and avoids harmful substances. This paper proposes a hybrid approach integrating the bacterial foraging optimization algorithm (BFOA) in a radial basis function neural network, applied to image classification, in order to improve the classification rate and the objective function value. At the beginning, the proposed approach is presented and described. Then its performance is studied with an accent on the variation of the number of bacteria in the population, the number of reproduction steps, the number of elimination-dispersal steps and the number of chemotactic steps of bacteria. By using various values of BFOA parameters, and after different tests, it is found that the proposed hybrid approach is very robust and efficient for several-image classification.

• Journal of Korean Institute of Industrial Engineers
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• v.27 no.1
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• pp.54-60
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• 2001

In this paper, a shape-based block layout (SBL) approach is presented to solve the facility layout problem with unequal-area and fixed shapes. The SBL approach employs hybrid genetic algorithm (Hybrid-GA) to find a good solution and the concept of bay structure is used. In the typical facility layout problem with unequal area and fixed shapes, the given geometric constraints of unequal-area and fixed shapes are mostly approximated to original shape by aspect ratio. Thus, the layout results require extensive manual revision to create practical layouts and it produces irregular building shapes and too much unusable spaces. Experimental results show that a SBL model is able to produce better solution and to create more practical layouts than those of existing approaches.

• IEMEK Journal of Embedded Systems and Applications
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• v.13 no.5
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• pp.261-268
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• 2018

Phase Change Memory(PCM) with low power consumption and high integration attracts attention as a next generation nonvolatile memory replacing DRAM. However, there is a problem that PCM has long latency and high energy consumption due to the writing operation. The PCM & DRAM hybrid memory structure is a fruitful structure that can overcome the disadvantages of such PCM. However, the page replacement algorithm is important, because these structures use two memory of different characteristics. The purpose of this document is to effectively manage pages that can be referenced in memory, taking into account the characteristics of DRAM and PCM. In order to manage these pages, this paper proposes an page replacement algorithm based on frequently accessed and recently paged. According to our simulation, the proposed algorithm for the DRAM&PCM hybrid can reduce the energy-delay product by around 10%, compared with Clock-DWF and CLOCK-HM.

• Journal of the Korean Institute of Telematics and Electronics
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• v.24 no.6
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• pp.1068-1073
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• 1987

Traditional circuit partitioning algorithm using the cluster development method, which is suitable for such applications as single chip floor planning or multiple layer PCB system placement, where the clusters are formed so that inter-cluster nets are localized within the I/O connector pins, may not be appropriate for the functiona block placement in truly 3-D electronic modules. 3-D hybrid IC is one such example where the inter-layer routing as well as the intra-layer routing can be maximally incorporated to reduce the overall circuit size, cooling requirements and to improve the speed performance. In this paper, we propose a new algorithm called MBE(Minimum Box Embedding) for the layer assignment of each functional block in 3-D hybrid IC design. The sequence of MBE is as follows` i) force-directed relaxation in 3-D space, ii) exhaustive search for the optimal orientation of the slicing plane and iii) layer assignment. The algorithm is first explaines for a 2-D reduced problem, and then extended for 3-D applications. An example result for a circuit consisting of 80 blocks has been shown.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2014.10a
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• pp.173-174
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• 2014

Vibration disturbances generated by reaction wheels may cause serious problems in high precision pointing spacecraft missions. Implementation of vibration isolator is a practical solution to meet the high pointing stability requirement placed on precision payloads. In this paper, development of hybrid vibration isolator that combines passive and active component is described. Vibration isolation performance of the developed isolator is evaluated using reaction wheel disturbance model. Hybrid isolation results obtained using FxLMS algorithm show clear improvement compared to the results obtained using only passive means.

• International Journal of Naval Architecture and Ocean Engineering
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• v.11 no.2
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• pp.809-818
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• 2019

The current trend in shipyard industry is to reduce the weight of ships to support the reduction of CO₂ emissions. In this study, the stiffened plate was optimized that is used for building most of the ship-structure. Further, this study proposed the hybrid Genetic Algorithm (GA) technique, which combines a genetic algorithm and subsequent optimization methods. The design variables included the number and type of stiffeners, stiffener spacing, and plate thickness. The number and type of stiffeners are discrete design variables that were optimized using the genetic algorithm. The stiffener spacing and plate thickness are continuous design variables that were determined by subsequent optimization. The plate deformation was classified into global and local displacement, resulting in accurate estimations of the maximum displacement. The optimization result showed that the proposed hybrid GA is effective for obtaining optimal solutions, for all the design variables.