• 전기학회논문지
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• 제56권9호
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• pp.1521-1526
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• 2007

This paper presents the application of Adaptive Evolutionary Algorithm (AEA) to search an optimal setting of overcurrent relay coordination to protect ring distribution systems. The AEA takes the merits of both a genetic algorithm (GA) and an evolution strategy (ES) in an adaptive manner to use the global search capability of GA and the local search capability of ES. The overcurrent relay settings and coordination requirements are formulated into a set of constraint equations and an objective function is developed to manage the overcurrent relay settings by the Time Coordination Method. The domain of overcurrent relays coordination for the ring-fed distribution systems is a non-linear system with a lot of local optimum points and a highly constrained optimization problem. Thus conventional methods fail in searching for the global optimum. AEA is employed to search for the optimum relay settings with maximum satisfaction of coordination constraints. The simulation results show that the proposed method can optimize the overcurrent relay settings, reduce relay mis-coordinated operations, and find better optimal overcurrent relay settings than the present available methods.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1991년도 한국자동제어학술회의논문집(국제학술편); KOEX, Seoul; 22-24 Oct. 1991
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• pp.1939-1943
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• 1991

Path planning is an important task for optimal motion of a robot in structured or unstructured environment. The goal of this paper is to plan the shortest collision-free path in 3D, when a robot is navigated to pick up some tools or to repair some parts from various locations. To accomplish the goal of this paper, the Path Coordinator is proposed to have the capabilities of an obstacle avoidance strategy[3] and a traveling salesman problem strategy(TSP)[23]. The obstacle avoidance strategy is to plan the shortest collision-free path between each pair of n locations in 2D or in 3D. The TSP strategy is to compute a minimal system cost of a tour that is defined as a closed path navigating each location exactly once. The TSP strategy can be implemented by the Neural Network. The obstacle avoidance strategy in 2D can be implemented by the VGraph Algorithm. However, the VGraph Algorithm is not useful in 3D, because it can't compute the global optimality in 3D. Thus, the Path Coordinator is proposed to solve this problem, having the capabilities of selecting the optimal edges by the modified Genetic Algorithm[21] and computing the optimal nodes along the optimal edges by the Recursive Compensation Algorithm[5].

• 한국정보통신학회논문지
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• 제15권9호
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• pp.1895-1902
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• 2011

Chase 알고리즘 기반의 연판정 e-BCH 복호 방식은 차세대 DVB-RCS 표준화에 오류 정정 부호화 방식으로 체택되었다. 구현을 위해서는 기존의 경판정 BCH 복호기와는 달리, 특히 연판정 e-BCH 복호시 필요한 양자화 비트수는 구현을 위해 반드시 결정해야 하며, 성능적인 측면에서도 만족을 해야만 한다. 따라서 본 논문에서는 DVB-RCSNG에서 채택된 연판정 e-BCH 복호기에서 구현을 위해 최적의 비트수를 BER 성능을 이용하여 설정하였다.

• 한국정보통신학회논문지
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• 제9권2호
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• pp.454-461
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• 2005

텔레매틱스의 주요 응용분야인 차량 항법 시스템은 CIS의 지도기술과 CPS의 측위 기술에 융합되어 탄생한 것이다. 기존의 시스템들은 정점과 정점간의 최단경로를 중심으로 한 경로 탐색을 제시하였지만 교통량의 변화와 교통사고 및 수시 병목 구간 등의 교통 변화에 대해서는 능동적인 대처를 할 수 없는 시스템이다. 바꿔 말하면 현실적으로 최단경로 탐색보다는 교통 정보를 파악하며 최단시간에 목적지로 도착하는 최적경로 탐색 시스템이 필요하다. 이 논문에서는 교통 정보를 기반으로 최적경로를 탐색하는 알고리즘을 제안한다. 구체적으로 최적 경로 탐색을 위한 시스템 구조를 제안하며 기존의 최단경로 탐색 알고리즘의 문제점을 살펴보고 수집되는 교통정보의 방향성을 활용하는 최적경로 탐색 알고리즘을 새롭게 제안한다.

• 대한전기학회논문지:시스템및제어부문D
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• 제54권3호
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• pp.148-155
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• 2005

A seam-line determination algorithm is proposed to determine image border-line in mosaicing using the transformation of gray value differences and dynamic programming. Since visually good border-line is the one along which pixel differences are as small as possible, it can be determined in association with an optimal path finding algorithm. A well-known effective optimal path finding algorithm is the Dynamic Programming (DP). Direct application of the dynamic programming to the seam-line determination causes the distance effect, in which seam-line is affected by its length as well as the gray value difference. In this paper, an adaptive cost transform algorithm with which the distance effect is suppressed is proposed in order to utilize the dynamic programming on the transformed pixel difference space. Also, a figure of merit which is the summation of fixed number of the biggest pixel difference on the seam-line (SFBPD) is suggested as an evaluation measure of seamlines. The performance of the proposed algorithm has been tested in both quantitively and visually on various kinds of images.

• 한국지능시스템학회논문지
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• 제18권2호
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• pp.212-215
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• 2008

본 논문에서 개선된 Dijkstra 알고리즘과 입자 군집 최적화를 이용한 최적 경로 계획 알고리즘을 제안한다. 최적의 경로를 구하기 위해 우선 이동 로봇 공간에서 MAKLINK를 작성하고 MAKLINK와 관련한 그래프를 얻는다. 여기서 MAKLINK는 장애물의 꼭지점을 연결하면서 볼록집합이 만들어지도록 하는 모서리의 집합을 의미한다. 얻은 그래프에서 출발점과 도착점을 포함하여 Dijkstra 알고리즘을 이용하여 최소 비용 최적 경로를 얻고 이 최적의 경로에서 개선된 Dijkstra경로를 얻는다. 마지막으로 개선된 Dijkstra경로에서 입자 군집 최적화를 적용하여 최적의 경로를 얻는다. 제안된 방법이 논문[1]에 나온 결과보다 더 좋은 성능을 갖는다는 것을 실험을 통해 입증한다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2007년도 심포지엄 논문집 정보 및 제어부문
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• pp.155-156
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• 2007

This paper presents the vision-based camber and optimal cutting line detection algorithm for hot-rolling process. It is important to measure the camber of head and tail part of strips because many problems are caused by the camber in the hot-rolling process. The hot-rolling process has time constraints. The camber detection algorithm of head and tail parts requires fast and less complex for satisfying time constraints. The proposed algorithm consists of two parts: measurement of the camber in the head and tail part of strips and decision part of the optimal cutting line of hot-rolled strip. First, we obtain the camber value of the strip from the difference between the real center line and the center line of head, tail part. Second, the head and tail part of strips isn't suitable for strips connections. Therefore, the cutting process is needed in the hot-rolling process. The optimal cutting line is determined by the head and tail images obtained from cameras. The algorithm is applied into the vision system with two area cameras, Matrox image processing board and host PC for verification.

• 대한전기학회논문지:전력기술부문A
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• 제50권9호
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• pp.424-430
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• 2001

A multi-level optimal power flow(OPF) algorithm has been evolved from a simple two stage optimal Power flow algorithm for constrained power economic dispatch control. In the proposed algorithm, we consider various constraints such as ower balance, generation capacity, transmission line capacity, transmission losses, security equality, and security inequality constraints. The proposed algorithm consists of four stages. At the first stage, we solve the aggregated problem that is the crude classical economic dispatch problem without considering transmission losses. An initial solution is obtained by the aggregation concept in which the solution satisfies the power balance equations and generation capacity constraints. Then, after load flow analysis, the transmission losses of an initial generation setting are matched by the slack bus generator that produces power with the cheapest cost. At the second stage we consider transmission losses. Formulation of the second stage becomes classical economic dispatch problem involving the transmission losses, which are distributed to all generators. Once a feasible solution is obtained from the second stage, transmission capacity and other violations are checked and corrected locally and quickly at the third stage. The fourth stage fine tunes the solution of the third stage to reach a real minimum. The proposed approach speeds up the two stage optimization method to an average gain of 2.99 for IEEE 30, 57, and 118 bus systems and EPRI Scenario systems A through D testings.

• 대한조선학회논문집
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• 제45권6호
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• pp.646-655
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• 2008

A main issue about production management of shipyards is to efficiently manage the work in process and logistics. However, so far the management of a transporter for moving building blocks has not been efficiently performed. To solve the issues, optimal block transporting scheduling system is developed for minimizing of the travel distance without overload of a transporter. To implement the developed system, a hybrid optimization algorithm for an optimal block transportation scheduling is proposed by combining the genetic algorithm and the ant algorithm. Finally, to evaluate the applicability of the developed system, it is applied to a block transportation scheduling problem of shipyards. The result shows that the developed system can generate the optimal block transportation scheduling of a transporter which minimizes the travel distance without overload of the transporter.

• 한국소음진동공학회논문집
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• 제25권10호
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• pp.677-684
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• 2015

It is often necessary to predict the vibration patterns of the structures from the signals of finite number of vibration sensors. This study presents the optimal placement of vibration sensors by applying the genetic algorithm and the modal expansion method. The modal expansion method is used to estimate the vibration response of the whole structure. The genetic algorithm is used to estimate the optimal placement of vibration sensors. Optimal sensor placement can be obtained so that the fitness function is minimized in the genetic algorithm. This paper discusses the comparison of the performances of two types of fitness functions, modal assurance criteria(MAC) and condition number( CN). As a result, the estimation using MAC shows better performance than using CN.