• Journal of the Economic Geographical Society of Korea
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• v.11 no.3
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• pp.459-475
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• 2008

This study analyzes the network structure of the Metropolitan Seoul subway system by applying complex network analysis methods. For the purpose, we construct the Metropolitan Seoul subway system as a network graph, and then calculate various indices introduced in complex network analysis. Structural characteristics of Metropolitan Seoul subway network are discussed by these indices. In particular, this study determines the shortest paths between nodes based on the weighted distance (physical and time distance) as well as topological network distance, since urban travel movements are more sensitive for them. We introduce an accessibility measurement based on the shortest distance both in terms of physical distance and network distance, and then compare the spatial structure between two. Accessibility levels of the system have been getting up overall, and thus the accessibility gaps have been getting lessen between center located subway stops and remote ones during the last 10 years. Passenger traffic volumes are explored from real passenger transaction databases by utilizing data mining techniques, and mapped by GIS. Clear differences reveal between the spatial patterns of real passenger flows and accessibility. That is, passenger flows of the Metropolitan Seoul subway system are related with population distribution and land use around subway stops as well as the accessibility supported by the subway network.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.5
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• pp.592-598
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• 2008

This paper presents collision prediction and avoidance method for AGVS (Automatic Guide Vehicle System). Also, we propose the PO(Right of Path Occupying) with decentralized delay time for collision avoidance. Classified essential element of AGV's working environment is modeled in this paper. Using this model, we propose a new shortest path algorithm using A* search algorithm and obtain the information on AGVs travel time, coordinates and rotation vector. Finally, we use the AGVs information data as input for simulation program. The simulation practice is used in order to evaluate a collision prediction and avoidance, and it has been presented to demonstrate the applicability of the minimize delay time.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.599-602
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• 2014

Proposal algorithm in this thesis introduced cells, units of router group, for distributed processing of previous genetic algorithm. This thesis presented ways to reduce search delay time of overall network through cell-based genetic algorithm. With regard to procedures of proposal algorithm, duplicated agents were transferred to the point, where the second, third, and fourth cells were created in order, after the first cell was made, and the agents were engineered to search the shortest path to each cell, and then find the most efficient element through competition.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39C no.9
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• pp.767-773
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• 2014

An economic ship routing means to sail a ship with a goal of minimizing the fuel consumption by utilizing weather forecast information, and there have been various systems which have been recently studied. For a successful economic ship routing system, it is needed to properly control an engine power or change a geographical path considering weather forecast. An optimal geographical path is difficult to be determined, though, because it is a minimal dynamic-cost path search problem where the actual fuel consumption is dynamically variable by the weather condition when the ship will pass the area. In this paper, we propose an geographical path-search algorithm based on evolutionary strategy to efficiently search a good quality solution out of tremendous candidate solutions. We tested our approach with the shortest path-based sailing method over seven testing routes and observed that the former reduced the estimated fuel consumption than the latter by 1.82% on average and the maximum 2.49% with little difference of estimated time of arrival. In particular, we observed that our method can find a path to avoid bad weather through a case analysis.

• Proceedings of the Korean Information Science Society Conference
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• 2005.07b
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• pp.595-597
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• 2005

본 논문에서는 자율 에이전트에 의해 미지의 공간을 탐사하는 실시간 그래프 탐색 알고리즘 DFS-RTA*와 DFS-PHA*를 제안하고 그 효율성을 비교한다. 두 알고리즘들은 모두 깊이-우선 탐색(DFS)을 기초로 하고 있으며, 직전 노드로의 빠른 후진(backtrack) 을 위해 각각 실시간 최단 경로 탐색 방법인 RTA*와 PHA*를 적용하는 것이 특징이다. 본 논문에서는 대표적인 3차원 온라인 게임 환경인 Unreal Tournament 게임과 지능형 캐릭터 에이전트인 KGBot를 이용한 실험을 통해 두 탐색 알고리즘의 완전성과 효율성을 분석해본다.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2005.05a
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• pp.222-231
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• 2005

본 논문에서는 자율 에이전트에 의해 미지의 공간을 탐사하는 실시간 그래프 탐색 알고리즘 $DFS-RTA^{\ast}$와 $DFS-PHA^{\ast}$를 제안하고 그 효율성을 비교한다. 두 알고리즘들은 모두 깊이-우선 탐색(DFS)을 기초로 하고 있으며, 직전 노드로의 빠른 후진(backtrack) 을 위해 각각 실시간 최단 경로 탐색 방법인 $RTA^{\ast}$와 $PHA^{\ast}$를 적용하는 것이 특징이다. 본 논문에서는 대표적인 3차원 온라인 게임 환경인 Unreal Tournament 게임과 지능형 캐릭터 에이전트인 KGBot를 이용한 실험을 통해 두 탐색 알고리즘의 완전성과 효율성을 분석해본다.

• KIISE Transactions on Computing Practices
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• v.20 no.12
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• pp.652-657
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• 2014

Given a starting point, destination point and various Points Of Interest (POIs), which contain a full or partial order, for a user to visit we wish to create, a sequenced route from the starting point to the destination point that includes one member of each POI type in a particular order. This paper proposes a method for finding the approximate shortest route between the start point, destination point and one member of each POI type. There are currently two algorithms that perform this task but they both have weaknesses. One of the algorithms only considers the distance between the visited POI (or starting point) and POI to visit next. The other algorithm chooses candidate points near the straight-line distance between the start point and destination but does not consider the order of visits on the corresponding network path. This paper outlines an algorithm that chooses the candidate points that are nearer to the network path between the start point and destination using network search. The algorithm looks for routes using the candidate points and finds the approximate shortest route by assigning an adaptive priority to the route that visits more POIs in a short amount of time.

• The Journal of Bigdata
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• v.7 no.2
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• pp.129-137
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• 2022

With the development of the 4th industry, the logistics industry is evolving into a smart logistics system. However, ship work that transports vehicles is progressing slowly due to various problems. In this paper, we propose an stowage automation algorithm that can be used for cargo loading of vehicle carriers that shortens loading and unloading work time. The stowage automation algorithm returns the shortest distance by searching for a loading space and a movable path in the ship in consideration of the structure of the ship. The algorithm identifies walls, ramps and vehicles that have already been shipped, and can work even with randomly placed. In particular, it is expected to contribute to developing a smart logistics system for vehicle carriers by referring to the ship's master plan to search for vehicle loading and unloading space in each port and predict the shortest movable path.

• Proceedings of the Korea Information Processing Society Conference
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• 2020.11a
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• pp.556-559
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• 2020

최근 태풍, 지진, 산불, 산사태, 전쟁 등 다양한 재난 상황으로 인한 인명피해와 자금 손실이 꾸준히 발생하고 있고 현재 이를 예방하고 복구하기 위해 많은 인력과 자금이 소요되고 있는 실정이다. 이러한 여러 재난 상황을 미리 감시하고 재난 발생의 빠른 인지 및 대처를 위해 본 논문에서는 인공지능 기반의 재난 드론 시스템을 설계 및 개발하였다. 본 연구에서는 사람이 감시하기 힘든 지역에 여러 대의 재난 드론을 이용하며 딥러닝 기반의 최단 경로 알고리즘을 적용해 각각의 드론이 최적의 경로로 효율적 탐색을 실시한다. 또한 드론의 근본적 문제인 배터리 용량 부족에 대한 문제점을 해결하기 위해 Ant Colony Optimization (ACO) 기술을 이용하여 각 드론의 최적 경로를 결정하게 된다. 제안한 시스템 구현을 위해 여러 재난 상황 중 산불 상황에 적용하였으며 전송된 데이터를 기반으로 산불지도를 만들고, 빔프로젝터를 탑재한 드론이 출동한 소방관에게 산불지도를 시각적으로 보여주었다. 제안한 시스템에서는 여러 대의 드론이 최적 경로 탐색 및 객체인식을 동시에 수행함으로써 빠른 시간 내에 재난 상황을 인지할 수 있다. 본 연구를 바탕으로 재난 드론 인프라를 구축하고 조난자 탐색(바다, 산, 밀림), 드론을 이용한 자체적인 화재진압, 방범 드론 등에 활용할 수 있다.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2007.04a
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• pp.161-164
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• 2007

우리는 알지 못하는 장소를 찾기 위해 네비게이션을 이용한다. 아직은 단순히 최단거리를 알려주는 네비게이션이 주를 이루고 있다. 하지만 그 길이 최적의 경로가 되는 것은 아니다. 이 논문에서는 이러한 점을 보완하기 위한 새로운 방법을 제시하고 있다. RFID 리더기와 카드를 이용하여 이용자의 출입을 체크함으로써 실시간으로 변하는 각 장소의 인원현황을 알 수 있다. 그리고 거리, 혼잡도, 선호도 등의 몇 가지 정보들을 토대로 퍼지와 유전자 알고리즘을 기반으로 하는 TSP를 이용하여 각각의 이용자 성향에 맞는 최적의 경로를 알 수 있다. 접근성을 높이기 위해 최적의 경로를 보여주는 디스플레이를 장착한 로봇을 이용한다. 다양한 컨텐츠를 포함시키면 더욱 발전한 안내 시스템으로서의 구현이 가능하다.