• 한국철도학회:학술대회논문집
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• 한국철도학회 1998년도 추계학술대회 논문집
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• pp.280-287
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• 1998

In this paper, Dynamic Fault Tree algorithm(DFT algorithm) is presented. This new algorithm provides a concise representation of dynamic fault tolerance system structure with redundancy, dynamic redundancy management and complex fault ＆ error recovery techniques. And it allows the modeler to define a dynamic fault tree model with the relative advantages of both fault tree and Markov models that captures the system structure and dynamic behavior. This algorithm applies to TMR and Dual-Duplex systems with the dynamic behavior and show that this algorithm captured the dynamic behavior in these systems with fault ＆ error recovery technique, sequence-dependent failures and the use dynamic spare. The DFT algorithm for solving the problems of the systems is more effective than the Markov and Fault tree analysis model.

• 전자공학회논문지S
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• 제34S권1호
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• pp.54-64
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• 1997

In this paper, a method of dynamic modeling and a dynamic control of a mobile robot are presented to show the superiority of the dynamic control comparing to the PD control. This dynamic model is derived from the cartesian coordinates using lagrange equations. Based upon the derived dynamic model, we implemented the dynamic control of the mobile robot using the computed torque method. Time varying non-linear friction terms are not incroporated in this dynamic model. Instead, those are considered as disturbances. This uncertainty in dynamic model of mobile robot is compensated by the outer loop controller using PD algorithm. The validity of this model and the control algorithm are confirmed through the experiments, where the dynamic control algorithm demonstrated robust velocity tracking performance against the unmodeled non-linear frictions. The superiority of this algorithm is demonstrated by comparing to classical PD control algorithm.

• 한국경영과학회지
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• 제27권2호
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• pp.97-109
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• 2002

Manufacturing environments in the real world are subject to many sources of change and uncertainty, such as new job releases, job cancellations, a chance in the processing time or start time of some operation. Thus, the realistic scheduling method should Properly reflect these dynamic environment. Based on the release times of jobs, JSSP (Job Shoe Scheduling Problem) can be classified as static and dynamic scheduling problem. In this research, we mainly consider the dynamic JSSP with continually arriving jobs. The goal of this research is to develop an efficient scheduling method based on GA (Genetic Algorithm) to address dynamic JSSP. we designed scheduling method based on SGA (Sing1e Genetic Algorithm) and PGA (Parallel Genetic Algorithm) The scheduling method based on GA is extended to address dynamic JSSP. Then, This algorithms are tested for scheduling and rescheduling in dynamic JSSP. The results is compared with dispatching rule. In comparison to dispatching rule, the GA approach produces better scheduling performance.

• 전기학회논문지
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• 제59권3호
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• pp.651-656
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• 2010

This paper proposes a new dynamic PCA algorithm to recognize types of electric poles, which is necessary for a mobile robot moving along the neutral line for inspecting high-voltage facilities. Since the mobile robot needs to pass over the electric poles and grasp the neutral wire again for the next region inspection, the detection of the electric pole type is a critical factor for the successful passing-over the electric pole. The CCD camera installed on the mobile robot captures the image of the electric pole while it is approaching to the electric pole. Applying the dynamic PCA algorithm to the CCD image, the electric pole type has been classified to provide the stable grasping operation for the mobile robot. The new dynamic PCA algorithm replaces the reference image in real time to improve the robustness of the PCA algorithm, adjusts the brightness to get the clear images, and applies the Laplacian edge detection algorithm to increase the recognition rate of electric pole type. Through the real experiments, the effectiveness of this proposed dynamic PCA algorithm method using Laplacian edge detecting method has been demonstrated, which improves the recognition rate about 20% comparing to the conventional PCA algorithm.

• 한국통신학회논문지
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• 제24권10A호
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• pp.1546-1554
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• 1999

본 논문에서는 결함 및 마스크, 스위칭 기능을 포함한 결함에 대한 동적 구조를 갖는 결함 허용 시스템에 대하여 신뢰도 평가를 할 수 있는 동적 결함 트리 알고리듬(Dynamic Fault Tree Algorithm)을 제안한다. 본 알고리듬에서는 동적 특성을 표현할 수 있는 FDEP, CSP, SEQ, PAG 게이트 정의로부터 출발한다. 이러한 게이트의 정의는 시스템의 동적 특성을 만족시키기 위해 시스템의 상태증가를 유발하는 기존의 마코브 모델과 시스템의 정적 특성에 대해서만 평가 가능했던 결함 트리 모델에 대한 제약조건을 해결할 수 있었다. 본 논문에서는 제시한 알고리듬의 장점을 입증하기 위하여 동적 특성을 가지는 TMR(Triple Modular Redundancy) 시스템과 이중화 중복 시스템(Dual Duplex System)에 대해 기존의 알고리듬과 제시하는 알고리듬을 적용하여 신뢰성 평가를 수행한 후 이를 통해 제시하는 알고리듬이 동적 여분을 사용하는 시스템이나 순차 종속 고장들을 가지는 시스템, 결함과 오류의 복구 기술을 가지는 시스템들에 대해 우수함을 보여준다.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2003년도 춘계학술대회
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• pp.1262-1269
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• 2003

In structural optimization, static loads are generally utilized although real external forces are dynamic. Dynamic loads have been considered in only small-scale problems. Recently, an algorithm for dynamic response optimization using transformation of dynamic loads into equivalent static loads has been proposed. The transformation is conducted to match the displacement fields from dynamic and static analyses. The algorithm can be applied to large-scale problems. However, the application has been limited to size optimization. The present study applies the algorithm to shape optimization. Because the number of degrees of freedom of finite element models is usually very large in shape optimization, it is difficult to conduct dynamic response optimization with the conventional methods that directly threat dynamic response in the time domain. The optimization process is carried out via interfacing an optimization system and an analysis system for structural dynamics. Various examples are solved to verify the algorithm. The results are compared to the results from static loads. It is found that the algorithm using static loads transformed from dynamic loads based on displacement is valid even for very large-scale problems such as shape optimization.

• 대한기계학회논문집A
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• 제27권8호
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• pp.1363-1370
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• 2003

In structural optimization, static loads are generally utilized although real external forces are dynamic. Dynamic loads have been considered in only small-scale problems. Recently, an algorithm for dynamic response optimization using transformation of dynamic loads into equivalent static loads has been proposed. The transformation is conducted to match the displacement fields from dynamic and static analyses. The algorithm can be applied to large-scale problems. However, the application has been limited to size optimization. The present study applies the algorithm to shape optimization. Because the number of degrees of freedom of finite element models is usually very large in shape optimization, it is difficult to conduct dynamic response optimization with the conventional methods that directly threat dynamic response in the time domain. The optimization process is carried out via interfacing an optimization system and an analysis system for structural dynamics. Various examples are solved to verify the algorithm. The results are compared to the results from static loads. It is found that the algorithm using static loads transformed from dynamic loads based on displacement is valid even for very large-scale problems such as shape optimization.

• 한국정보과학회논문지:소프트웨어및응용
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• 제30권9호
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• pp.803-811
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• 2003

단백질들의 복수서열정렬은 단백질 서열간의 관계를 유추할 수 있는 유용한 도구이다. 최적화된 복수서열정렬을 얻기 위해 사용되는 가장 유용한 방법은 dynamic programming이다. 그러나 dynamic programming은 특정한 비용함수를 사용할 수 없기 때문에 특별한 경우 최소의 비용을 가지는 복수서열 정렬을 제공하지 못하는 문제점이 있다. 우리는 이러한 문제점을 해결하기 위하여 부분서열정렬 개선기법을 사용한 알고리즘을 제안하였으며, 이 알고리즘이 dynamic programming의 문제점을 효과적으로 해결함을 보였다.

• 제어로봇시스템학회논문지
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• 제5권2호
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• pp.189-199
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• 1999

This paper presents an optimization algorithm for a stable Self Dynamic Neural Network(SDNN) using genetic algorithm. Optimized SDNN is applied to a problem of controlling nonlinear dynamical systems. SDNN is dynamic mapping and is better suited for dynamical systems than static forward neural network. The real-time implementation is very important, and thus the neuro controller also needs to be designed such that it converges with a relatively small number of training cycles. SDW has considerably fewer weights than DNN. Since there is no interlink among the hidden layer. The object of proposed algorithm is that the number of self dynamic neuron node and the gradient of activation functions are simultaneously optimized by genetic algorithms. To guarantee convergence, an analytic method based on the Lyapunov function is used to find a stable learning for the SDNN. The ability and effectiveness of identifying and controlling a nonlinear dynamic system using the proposed optimized SDNN considering stability is demonstrated by case studies.

• 한국정보처리학회논문지
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• 제5권9호
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• pp.2323-2333
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• 1998

어떤 프로그램에서 오류가 발견되었을 때 프로그래머는 어떤 시험 사례(test-case)를 통해 프로그램을 분석한다. 이처럼 현재 입력 값에 영향을 끼치는 모든 명령문들에 관련된 동적 슬라이싱(dynamic slicing)과 이를 구현하는 기술은 실제 테스팅 및 디버깅 분야에서 매우 중요하다고 할 것이다. 본 논문에서는 이러한 동적 프로그램 슬라이스(dynamic program slices)를 산출하는 마킹 알고리즘을 제시하였고 이것을 프로그래밍한 뒤 예제 프로그램을 적용시켜 구현하였다. 구현 결과는 실행 이력에 대한 마킹 테이블(marking table), 동적 종속 그래프(Dynamic Dependence Graph) 그리고, 축소 동적 종속 그래프(Reduced Dynamic Dependence Graph)로 나타내었다. 그리고, 본 논문에서 제시한 효율적인 동적 슬라이스 생성을 위한 마킹 알고리즘과 동적 종속 그래프가 기존의 기법 보다 더 효율성이 높다는 것을 보였다.