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박상혁(Sanghyuk Park),홍주현(Ju-Hyeon Hong),하현종(Hyun-Jong Ha),유창경(Chang-Kyung Ryoo),신원영(Wonyoung Shin) 한국항공우주학회 2014 韓國航空宇宙學會誌 Vol.42 No.2
본 논문은 무인기의 생존성을 최대화하기 위한 경로점을 결정하는 기법을 제안한다. 본 논문에서 초기 경로점을 선정하기 위해 사용된 Voronoi diagram은 위협의 위치와 크기가 주어져 있을 때, 위협으로부터 최대한 멀리 피해서 가는 경로를 계획하는데 많이 이용되고 있는 기법이다. 하지만 위협의 크기가 서로 다르고, 비행경로가 직선경로로 계획되어야 한다면 실제 경로 계획 시 Voronoi diagram으로는 한계가 있다. 본 논문에서는 Voronoi diagram을 통해 선정한 초기 경로점을 위협의 형태에 맞춰 최적화를 수행하는 방식을 적용하였다. 각 경로점의 인접한 경로점들을 고정시킨 상태에서 경로점을 하나씩 최적화를 수행하는 방식으로 최적화를 수행하였다. 이 방식은 전체 경로점들이 수렴할 때 까지 국소최적화를 반복함으로써, 최적의 경로점을 찾기 위해 소요되는 연산시간을 크게 감소시켰다. This paper proposes a determination method of waypoints to maximize the survivability of a UAV. Voronoi diagram which is used for the initial selection of waypoint candidates is the most widely used path planning technique to avoid the threat as far as possible when the location and strength of the threat are given. But if threat strength is different each other and flight path is constrained along with straight lines, Voronoi diagram has limitations in real applications. In this study, the initial waypoints obtained from Voronoi diagram are optimized considering the shape of each threat. Here, a waypoint is optimized while adjacent waypoints are fixed. By repeating this localized optimization until whole waypoints are converged, computation time for finding the best waypoints is greatly reduced.
김인중(Injung Kim),나기현(Kihyun Na),양소희(Sohee Yang),장재민(Jaemin Jang),김윤종(Yunjong Kim),신원영(Wonyoung Shin),김덕중(Deokjung Kim) Korean Institute of Information Scientists and Eng 2017 정보과학회논문지 Vol.44 No.8
T-commerce is technology-fusion service on which the user can purchase using data broadcasting technology based on bi-directional digital TVs. To achieve the best revenue under a limited environment in regard to the channel number and the variety of sales goods, organizing broadcast programs to maximize the expected sales considering the selling power of each product at each time slot. For this, this paper proposes a method to predict the sales of goods when it is assigned to each time slot. The proposed method predicts the sales of product at a time slot given the week-in-year and weather of the target day. Additionally, it combines a statistical predict model applying SVD (Singular Value Decomposition) to mitigate the sparsity problem caused by the bias in sales record. In experiments on the sales data of W-shopping, a T-commerce company, the proposed method showed NMAE (Normalized Mean Absolute Error) of 0.12 between the prediction and the actual sales, which confirms the effectiveness of the proposed method. The proposed method is practically applied to the T-commerce system of W-shopping and used for broadcasting organization.