• Title/Summary/Keyword: Dijkstra 최단경로

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Case Study for Telecommunication Network Design based on Optimal Path Algorithm (최적경로 알고리듬을 활용한 경제적인 통신망 설계 적용 사례)

  • Jung, Ju-Young;Choi, Yun-Soo;Jun, Chul-Min;Cho, Seong-Kil
    • Journal of Korea Spatial Information System Society
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    • v.8 no.1 s.16
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    • pp.107-118
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    • 2006
  • In this paper, several network algorithms were tested to find an optimal one for telecommunication network design. Algorithms such as Dijkstra's shortest path algorithm, Ford-Bellman's shortest path algorithm, Prim's minimum spanning tree algorithm, and Kruscal's minimum spanning tree algorithm were reviewed and compared in terms of feasibility and resulted network construction cost. Then an optimal algorithm that is most suitable for telecommunication network design was selected. For more specific and quantitative analysis of the selected algorithm, it was implemented to a real telecommunication network construction site. The analyzed results showed that the suggested design method when compared with the conventional one, reduced the network construction cost considerably. The total network length estimated by the conventional method were 5267 meters while the suggested method resulted in 4807 meters. Thus the new method reduced the total network length by 8.7 percent which is equivalent to 97,469,000 Won of construction cost. Considering the frequent telecommunication network constructions, due to new urban developments in the nation, the economic benefit of the suggested telecommunication network design method will be significant. In addition to the construction cost savings, the suggested telecommunication network design procedure possesses several other economic benefits. Since the design procedure can be standardized and automatized, it can reduce the design cost itself and the skill acquirement periods required for new or inapt design crews. Further, due to the standardized and automatized design procedure, any telecommunication network design results can accessed more objectively.

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MDP(Markov Decision Process) Model for Prediction of Survivor Behavior based on Topographic Information (지형정보 기반 조난자 행동예측을 위한 마코프 의사결정과정 모형)

  • Jinho Son;Suhwan Kim
    • 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.