• Proceedings of the KIEE Conference
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• 2008.10a
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• pp.75-76
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• 2008

전력거래소는 전격계통 안정된 운영과 공정한 전력시장 운영을 주요 임무로 하며, 이를 위하여 전국의 80여개의 발전소와 600여개 변전소로부터 발전량, 전압, 조류, 자단기 상태정보 등 다양한 전력계통 자료를 취득하고 있다 전력거래소의 중앙급전소에는 이와 같은 계통자료 취득은 물론 발전량 제어기능을 수행하기 위한 에너지관리시스템(이하 EMS 라 한다)을 운영하고 있으며, 발,변전소에는 현장의 전력설비와 연결되어 계통자료를 취득하여 EMS로 전송하는 원격소장치 (이하 RTU 라한다)를 운영하고 있다. 자료취득 경로는 모든 발전소와 34skv급 이상의 변전소의 경우 EMS와 RTU가 직접 연결되어 자료를 취득하며 154Kv급 이하 변전소는 12개 지역급전소의 자료취득제어시스템(이하 SCADA라 한다)를 경유하여 자료를 취득하고 있다. 전력계통의 대형화와 복잡화에 따라 계통해석기능 자동발전제어기능에 의한 계류운영으로 정보기술에 대한 의존도가 증가하고 있으며, 변동비 반영시장의 개선운영에 따라 공정한 전력시장 운영과 안정된 전력계통 운영을 위해 전력계통 취득자료의 신뢰도가 요구되고 있다. 따라서 EMS를 비롯한 RTU, 통신망 등 전력계통 자료취득 설비의 운영실적을 분석하여 각 시스템별 고장 고장원인 고장유형 등을 고찰하므로써 시스템 성능개선을 위한 설비투자와 운영개선에 반영하고자 한다.

• Proceedings of the Korean Information Science Society Conference
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• 2008.06a
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• pp.164-165
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• 2008

전장에서 임무 수행중인 병력이나 탱크 등을 지원하거나 보호 동물의 활동을 모니터링 하는 센서 네트워크에서는 전송 정보뿐만 아니라 그러한 대상들의 위치를 악의적 추적자로부터 보호할 수 있어야 한다. 본 논문에서는 활동 소오스 노드처럼 메시지 전송은 진행하고 있지 않지만 위치가 보호되어야 할 대상과 근접한 휴면(dormant) 소오스 노드들을 고려한 소오스 위치 보호 라우팅 기법 GSLP(GPSR-based Source-Location Privacy)를 제안한다. GSLP는 알고리즘의 간결성과 신장성(scalability)이 뛰어난 GPSR(greedy perimeter stateless routing)을 확장하여 메시지 전달 노드를 선정할 때 일정 확률로 임의의 이웃 노드를 선택하는 한편, perimeter 라우팅을 적용하여 소오스 노드들을 우회하도록 하여 위치를 보호하도록 하였다. 시뮬레이션 결과, 기존의 대표적인 소오스 위치 보호 라우팅 프로토콜인 PR-SP(Phantom Routing-Single Path)에 비해 GSLP는 휴면 소오스 노드들의 수에 거의 관계없이 높은 안전 기간(전송 메시지 수)을 일정하게 제공하면서도 전달 지연(경로의 평균 홉(hop) 수)은 도착지와의 최단 홉 수의 약 두 배 이내에 머물러 대규모 센서 네트워크에서의 소오스의 위치를 보호하기 위한 방안으로 적합한 것으로 평가되었다.

• Journal of Advanced Navigation Technology
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• v.16 no.2
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• pp.271-277
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• 2012

In this paper, we propose a dynamic tree formation protocol for multiple UAV which is gathering data or accomplishing a mission such as disaster monitoring, environment monitoring, and disaster relief. Especilly, we designed Hop-LQI Weight algorithm to form optimal tree in wireless dynamic environment applying situation of radio signal attenuation over distance and implemented our algorithm in MSP 430 K-mote sensor platform using TinyOS codes. We verified performance of our algorithm by comparing average link setup time by the number of nodes with minimum LQI, link cost calculation method in wireless communication.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.40 no.7
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• pp.590-600
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• 2012

In this research, generalized sizing methods were studied that can be applied to an aircraft which uses solar cell or fuel cell as energy sources. To consider multiple propulsion systems and energy resources, multiple power paths were modeled and the weight of consumable and non-consumable energy was reflected in the weight change calculation for each mission segments. In the constraint analysis, power to weight ratio was selected instead of thrust to weight ratio and used in the sizing process of balancing power and energy.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.9 no.6
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• pp.1574-1580
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• 2008

In this paper, to bring under robust and accurate control of auto-equipment systems which disturbance, parameter alteration of system, uncertainty and so forth exist, neural network controller called dynamic neural processor(DNP) is designed In order to perform a elaborate task like as assembly, manufacturing and so forth of components, tracking control on the trajectory of power coming in contact with a target as well as tracking control on the movement course trajectory of end-effector is indispensable. Also, the learning architecture to compute inverse kinematic coordinates transformations in the Plants of auto-equipment systems is developed and the example that DNP can be used is explained. The architecture and learning algorithm of the proposed dynamic neural network, the DNP, are described and computer simulations are provided to demonstrate the effectiveness of the proposed learning method using the DNP.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.2
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• pp.218-224
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• 2012

Recently, as the needs of developing the micro autonomous underwater vehicle (AUV) are increasing, the acquisition of the elementary technology is urgent. While they mostly utilizes information of the forward looking sonar (FLS) in conventional studies of the local path control as an elementary technology, it is desirable to use the obstacle avoidance sonar (OAS) because the size of the FLS is not suitable for the micro AUV. In brief, the local path control system based on the OAS for the micro AUV operates with the following problems: the OAS offers low bearing resolution and local range information, it requires the system that has reduced power consumption to extend the mission execution time, and it requires an easy design procedure in terms of its structures and parameters. To solve these problems, an intelligent local path control algorithm based on the beam modeling of OAS with the evolution strategy (ES) and the fuzzy logic controller (FLC), is proposed. To verify the performance and analyze the characteristic of the proposed algorithm, the course control of the underwater flight vehicle (UFV) is performed in the horizontal plane. Simulation results show that the feasibility of real application and the necessity of additional work in the proposed algorithm.

• Journal of the Korea Society for Simulation
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• v.33 no.2
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• pp.37-44
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• 2024

The Korean Helicopter Development Program has successfully introduced the Surion helicopter, a versatile multi-domain operational aircraft that replaces the aging UH-1 and 500MD helicopters. Specifically designed for maneuverability, the Surion plays a crucial role in low-altitude tactical maneuvers for personnel transportation and specific missions, emphasizing the helicopter's survivability. Despite the significance of its low-altitude tactical maneuver capability, there is a notable gap in research focusing on multi-mission tactical maneuvers that consider the risk factors associated with deploying the Surion in the presence of enemy air defenses. This study addresses this gap by exploring a method to enhance the Surion's low-altitude maneuvering paths, incorporating information about enemy air defenses. Leveraging the Proximal Policy Optimization (PPO) algorithm, a reinforcement learning-based approach, the research aims to optimize the helicopter's path planning. Visualized experiments were conducted using a Surion model implemented in the Unity environment and ML-Agents library. The proposed method resulted in a rapid and stable policy convergence for generating optimal maneuvering paths for the Surion. The experiments, based on two key criteria, "operation time" and "minimum damage," revealed distinct optimal paths. This divergence suggests the potential for effective tactical maneuvers in low-altitude situations, considering the risk factors associated with enemy air defenses. Importantly, the Surion's capability for remote control in all directions enhances its adaptability in complex operational environments.

• Journal of Korean Society of Transportation
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• v.22 no.5
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• pp.89-97
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• 2004

The Korea Air Force(KAF) has operated freight flights based on the prefixed time and route schedule, which is adjusted once in a month. The major purpose of the operation of freight flights in the KAF is to distribute necessary supplies from the home air base to other air bases. The secondary purpose is to train the young pilots to get more experiences in navigation. Each freight flight starts from and returned to the home air base everyday except holidays, while it visits several other air bases to accomplish its missions. The study aims to forecast freight demand at each base by using time series analysis, and then it tried to optimize the cost of operating flights by solving vehicle routing problem. For more specifically, first, several constraints in operating cargos were defined by reviewing the Korea Air Force manuals and regulation. With such constraints, an integer programming problem was formulated for this specific routing problem allowing several visits in a tour with limitation of maximum number of visits. Then, an algorithm to solve the routing problem was developed. Second, the time series analysis method was applied to find out the freight demand at each air base from the mother air base in the next month. With the forecasted demands and the developed solution algorithm, the oprimum routes are calculated for each flight. Finally, the study compared the solved routing system by the developed algorithm with the existing routing system of the Korea Air Force. Through this comparison, the study proved that the proposed method can provide more (economically) efficient routing system than the existing system in terms of computing and monetary cost. In summary, the study suggested objective criteria for air routing plan in the KAF. It also developed the methods which could forecast properly the freight demands at each bases by using time series analysis and which could find the optimum routing which minimizes number of cargo needed. Finally, the study showed the economical savings with the optimized routing system by using real case example.

• The Journal of the Korea Contents Association
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• v.5 no.5
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• pp.1-9
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• 2005

In this paper, we suggest multi colony interaction ant reinforcement learning model. This method is a hybrid of multi colony interaction by elite strategy and reinforcement teaming applying Temporal Difference(TD) learning to Ant-Q loaming. Proposed model is consisted of some independent AS colonies, and interaction achieves search according to elite strategy(Intensification, Diversification strategy) between the colonies. Intensification strategy enables to select of good path to use heuristic information of other agent colony. This makes to select the high frequency of the visit of a edge by agents through positive interaction of between the colonies. Diversification strategy makes to escape selection of the high frequency of the visit of a edge by agents achieve negative interaction by search information of other agent colony. Through this strategies, we could know that proposed reinforcement loaming method converges faster to optimal solution than original ACS and Ant-Q.

• Journal of Intelligence and Information Systems
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• v.29 no.2
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• pp.101-114
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• 2023

In the wartime, aircraft carrying out a mission to strike the enemy deep in the depth are exposed to the risk of being shoot down. As a key combat force in mordern warfare, it takes a lot of time, effot and national budget to train military flight personnel who operate high-tech weapon systems. Therefore, this study studied the path problem of predicting the route of emergency escape from enemy territory to the target point to avoid obstacles, and through this, the possibility of safe recovery of emergency escape military flight personnel was increased. based problem, transforming the problem into a TSP, VRP, and Dijkstra algorithm, and approaching it with an optimization technique. However, if this problem is approached in a network problem, it is difficult to reflect the dynamic factors and uncertainties of the battlefield environment that military flight personnel in distress will face. So, MDP suitable for modeling dynamic environments was applied and studied. In addition, GIS was used to obtain topographic information data, and in the process of designing the reward structure of MDP, topographic information was reflected in more detail so that the model could be more realistic than previous studies. In this study, value iteration algorithms and deterministic methods were used to derive a path that allows the military flight personnel in distress to move to the shortest distance while making the most of the topographical advantages. In addition, it was intended to add the reality of the model by adding actual topographic information and obstacles that the military flight personnel in distress can meet in the process of escape and escape. Through this, it was possible to predict through which route the military flight personnel would escape and escape in the actual situation. The model presented in this study can be applied to various operational situations through redesign of the reward structure. In actual situations, decision support based on scientific techniques that reflect various factors in predicting the escape route of the military flight personnel in distress and conducting combat search and rescue operations will be possible.