• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.4
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• pp.97-104
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• 2018

In the conventional direction finding, the antenna is installed at a high position on the ground to detect the position of the target with the environment of the LOS(Line of Sight) as much as the signal receiving environment. However, in order to configure such environment, high cost and installation time were required. In this paper, we use TDOA(Time Difference of Arrival) technique to utilize drones in direction finding, so that four drones can be used for directions finding simulation. Simulations based on drone and TDOA direction finding were constructed using additional signal processing Taylor series and Exact Interactive Algorithm. In the simulation, the receiving power is defined by using the 800MHz path-loss model using the GPS information of the ground direction detection, and the position estimation performance is analyzed when the TDOA technique, the Taylor series, and the Exact Interactive Alogrithm are applied.

• Industrial Engineering and Management Systems
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• v.15 no.1
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• pp.19-31
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• 2016

A design method of the network for automated transporters mounted on rails is addressed for automated container terminals. In the network design, the flow directions of some path segments as well as routes of transporters for each flow requirement must be determined, while the total transportation and waiting times are minimized. This study considers, for the design of the network, the waiting times of the transporters during the travel on path segments, intersections, transfer points below the quay crane (QC), and transfer points at the storage yard. An algorithm, which is the combination of a modified Dijkstra's algorithm for finding the shortest time path and a queuing theory for calculating the waiting times during the travel, is proposed. The proposed algorithm can solve the problem in a short time, which can be used in practice. Numerical experiments showed that the proposed algorithm gives solutions better than several simple rules. It was also shown that the proposed algorithm provides satisfactory solutions in a reasonable time with only average 7.22% gap in its travel time from those by a genetic algorithm which needs too long computational time. The performance of the algorithm is tested and analyzed for various parameters.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.1389-1391
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• 1996

In this paper, we applies two methods - Genetic Algorithm(GA) and $A^*$ Algorithm - to find the optimal path in route guidance system. Under the assumption that the traveling costs of each link are given, the task to find the optimal path becomes very complicated problem if the number of nodes or links increase. Two well-known algorithms are modified to resolve the problem and the preliminary demonstration show both optimistic result and needs to improvement.

• Journal of Korean Society of Transportation
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• v.23 no.7 s.85
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• pp.149-158
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• 2005

The object of this paper is to develop the shortest path algorithm. The existing shortest path algorithm models are developed while considering travel time and travel distance. A few problems occur in these shortest path algorithm models, which have paid no regard to cognition of users, such as when user who doesn't have complete information about the trip meets a strange road or when the route searched from the shortest path algorithm model is not commonly used by users in real network. This paper develops a shortest path algorithm model to provide ideal route that many people actually prefer. In order to provide the ideal shortest path with the consideration of travel time, travel distance and road cognition, travel time is predicted by using Kalman filtering and travel distance is predicted by using GIS attributions. The road cognition is considered by using space data of GIS. Optimal routes provided from this paper are shortest distance path, shortest time path, shortest path considering distance and cognition and shortest path considering time and cognition.

• Journal of Information Processing Systems
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• v.13 no.1
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• pp.104-113
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• 2017

In this paper, we present an approach to transmit data from the source to the destination through a minimal path (least-cost path) in a computer network of n nodes. The motivation behind our approach is to address the problem of finding a minimal path between the source and destination. From the work we have studied, we found that a Steiner tree with bounded Steiner vertices offers a good solution. A novel algorithm to construct a Steiner tree with vertices and bounded Steiner vertices is proposed in this paper. The algorithm finds a path from each source to each destination at a minimum cost and minimum number of Steiner vertices. We propose both the sequential and parallel versions. We also conducted a comparative study of sequential and parallel versions based on time complexity, which proved that parallel implementation is more efficient than sequential.

• Proceedings of the Korean Society of Computer Information Conference
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• 2010.07a
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• pp.103-107
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• 2010

게임이나 네비게이션 시스템, 관광경로 설계에 있어서 경로찾기는 매우 중요한 부분 중의 하나이다. 일반적으로 TSP(Traveling Salesman Problem), RPP(Rural Postman Problem), CPP(Chinese Postman Problem)와 같은 경로찾기 문제들은 일반적인 알고리즘으로 최적해를 구할 수 없다. 문제크기가 커질수록 해집합이 폭발적으로 커짐으로써 전체 해집합을 탐색하는데 많은 비용이 든다. 따라서, 이러한 문제들은 유전알고리즘이나 Simulated Annealing과 같은 휴리스틱 알고리즘을 이용하여 근사최적 경로를 찾는다. 본 논문에서는 이와 같은 경로찾기 문제의 근사 최적해를 구하기 위한 시뮬레이션 시스템을 설계하고 구현하였다. 본 연구에서 구현한 시뮬레이션 시스템에는 유전알고리즘 엔진(GA 엔진)과 사용자 인터페이스를 제공한다. 사용자 인터페이스는 유전알고리즘에 사용될 파라미터를 설정하는 부분이며, GA 엔진은 유전알고리즘의 연산자들을 제공하는 부분이다. 본 논문에서 구현한 시뮬레이션 시스템은 게임과 같은 경로찾기 등에 활용될 수 있다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.7B
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• pp.652-659
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• 2006

The routing algorithm is one of the key research areas in ad hoc networks. The most of existing routing algorithms depends on current availability of wireless link when finding the feasible path. Dependence on current information may mislead to a fragile communication path. Some routing approaches that take statistical average on received signal power enhance the possibility to find the most stable path, but have limitation on considering only the average power level. In this paper, we propose routing algorithm based on link stability for ad hoc network. The proposed algorithm not only takes statistical average, but also traces the degree of variations in received signal power. The simulation result support that the proposed algorithm is more likely to find the most stable path under the severe communication environment.

• Journal of KIISE
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• v.43 no.9
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• pp.1026-1033
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• 2016

Path-finding on a grid map is a problem generally addressed in the fields of robotics, intelligent agents, and computer games. As technology advances, virtual game worlds tend to be represented more accurately and more realistically, resulting in an excessive increase in the number of grid tiles and in path-search time. In this study, we propose a path-finding algorithm that allows a prompt response to real-time queries by constructing a reduced state space and by precomputing all possible paths in an offline preprocessing stage. In the preprocessing stage, we vertically decompose free space on the grid map, construct a connectivity graph where nodes are the decomposed regions, and store paths between all pairs of nodes in matrix form. In the real-time query stage, we first find the nodes containing the query points and then retrieve the corresponding stored path. The proposed method is simulated for a set of maps that has been used as a benchmark for grid-based path finding. The simulation results show that the state space and the search time decrease significantly.

• Proceedings of the KOR-KST Conference
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• 2007.05a
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• pp.159-168
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• 2007

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2008.10a
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• pp.182-187
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• 2008

It needs to consider of turns during a path-finding on real road network. traveling on real road network, it generally takes less travel time in a more straight path than a zig-zaged path with same source and destination. In this paper, we propose $VTA^*$ algorithm that can reduce the cost of exploring despite increasing the number of turn in comparing with $TA^*$ algorithm. We have implement the proposed $VTA^*$, $TA^*$ which consider the number of turn and a traditional $A^*$ algorithm which dosen't consider the number of turn. The experimental result shows that the cost of exploring is reduced by 7.31 % comparing with $TA^*$ and the number of turn is reduced by 27.95% comparing with $A^*$ approximately.