• 제목/요약/키워드: Spline tree

검색결과 13건 처리시간 0.023초

Multivariate Decision Tree for High -dimensional Response Vector with Its Application

  • Lee, Seong-Keon
    • Communications for Statistical Applications and Methods
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    • 제11권3호
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    • pp.539-551
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    • 2004
  • Multiple responses are often observed in many application fields, such as customer's time-of-day pattern for using internet. Some decision trees for multiple responses have been constructed by many researchers. However, if the response is a high-dimensional vector that can be thought of as a discretized function, then fitting a multivariate decision tree may be unsuccessful. Yu and Lambert (1999) suggested spline tree and principal component tree to analyze high dimensional response vector by using dimension reduction techniques. In this paper, we shall propose factor tree which would be more interpretable and competitive. Furthermore, using Korean internet company data, we will analyze time-of-day patterns for internet user.

전역 최적화를 위한 B-스플라인 기반의 Branch & Bound알고리즘 (A B-spline based Branch & Bound Algorithm for Global Optimization)

  • 박상근
    • 한국CDE학회논문집
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    • 제15권1호
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    • pp.24-32
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    • 2010
  • This paper introduces a B-spline based branch & bound algorithm for global optimization. The branch & bound is a well-known algorithm paradigm for global optimization, of which key components are the subdivision scheme and the bound calculation scheme. For this, we consider the B-spline hypervolume to approximate an objective function defined in a design space. This model enables us to subdivide the design space, and to compute the upper & lower bound of each subspace where the bound calculation is based on the LHS sampling points. We also describe a search tree to represent the searching process for optimal solution, and explain iteration steps and some conditions necessary to carry out the algorithm. Finally, the performance of the proposed algorithm is examined on some test problems which would cover most difficulties faced in global optimization area. It shows that the proposed algorithm is complete algorithm not using heuristics, provides an approximate global solution within prescribed tolerances, and has the good possibility for large scale NP-hard optimization.

실제지형을 고려한 고정익 무인항공기의 최적 경로계획 (Optimal Path Planner Considering Real Terrain for Fixed-Wing UAVs)

  • 이다솔;심현철
    • 제어로봇시스템학회논문지
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    • 제20권12호
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    • pp.1272-1277
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    • 2014
  • This article describes a path planning algorithm for fixed-wing UAVs when a real terrain should be considered. Nowadays, many UAVs are required to perform mission flights near given terrain for surveillance, reconnaissance, and infiltration, as well as flight altitude of many UAVs are relatively lower than typical manned aerial vehicles. Therefore, real terrain should be considered in path planning algorithms of fixed-wing UAVs. In this research, we have extended a spline-$RRT^*$ algorithm to three-dimensional planner. The spline-$RRT^*$ algorithm is a $RRT^*$ based algorithm, and it takes spline method to extend the tree structure over the workspace to generate smooth paths without any post-processing. Direction continuity of the resulting path is guaranteed via this spline technique, and it is essential factor for the paths of fixed-wing UAVs. The proposed algorithm confirm collision check during the tree structure extension, so that generated path is both geometrically and dynamically feasible in addition to direction continuity. To decrease degrees of freedom of a random configuration, we designed a function assigning directions to nodes of the graph. As a result, it increases the execution speed of the algorithm efficiently. In order to investigate the performance of the proposed planning algorithm, several simulations are performed under real terrain environment. Simulation results show that this proposed algorithm can be utilized effectively to path planning applications considering real terrain.

The Relationship between Tree-Ring Growth in Pinus densiflora S. et Z. and the Corresponding Climatic Factors in Korea

  • LEE, Kwang Hee;JO, Sang Yoon;KIM, Soo Chul
    • Journal of the Korean Wood Science and Technology
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    • 제50권2호
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    • pp.81-92
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    • 2022
  • To analyze the relationship between climatic factors (mean monthly temperature and total precipitation) and tree-ring growths of Pinus densiflora S. et Z. from National Parks (according to region) of the Korea, 20 trees were sampled from 13 National Parks. Only trees that were successfully cross-dated were used for dendrochronological analysis, and at least 11 trees were included. The tree-ring chronology of Mt. Bukhan (covering the shortest period of 1917 - 2016 [100 years]) was assessed, as well as that of Mt. Seorak (covering the longest period of 1687 - 2017 [331 years]). After cross-dating, each ring width series was double-standardized by first fitting a logarithmic curve and then a 50-year cubic spline. The relationships between climate and tree-ring growth were calculated with response function analysis. The results show a significant positive correlation between a given year's February-March temperature, May precipitation levels, and tree-ring growth. It indicates that a higher temperature in early spring and precipitation before cambium activity are important for radial growths of Pinus densiflora in the Korea.

지형적 특성에 따른 월악산 신갈나무의 연륜생장과 기후와의 관계 (Relationships between Climate and Tree-Ring Growths of Mongolian Oaks with Various Topographical Characteristics in Mt. Worak, Korea)

  • 서정욱;박원규
    • 한국환경복원기술학회지
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    • 제13권3호
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    • pp.36-45
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    • 2010
  • To analyze the relationship between climatic factors (monthly mean temperature and total precipitation) and tree-ring growths of Quercus mongolica Fischer (Mongolian oak) with different topographic sites in Mt. Worak, more than 10 trees were selected from each of seven stands. Two cores from each tree were measured for ring width. After crossdating, each ring-width series was double standardized by fitting first a negative exponential or straight regression line and secondly a 60-year cubic spline. Seven stands were categorized in two groups using cluster analysis for tree-ring index patterns. Cluster I (four stands) was located in higher elevation (550-812 m) with aspects of east, west and northwest, and cluster II (three stands) was located in rather lower election (330-628 m) with aspects of north and northwest. The aspects of two clusters were not significantly different. Response-function analysis showed a significant positive response to March precipitation for both clusters. It indicates that moisture supply during early spring season is important to radial growth because the cambial growths of ring-porous species, such as Mongolian oak, start before leaf growth. Cluster II showed a positive response to the precipitation of middle and late growing season, too.

Efficient point cloud data processing in shipbuilding: Reformative component extraction method and registration method

  • Sun, Jingyu;Hiekata, Kazuo;Yamato, Hiroyuki;Nakagaki, Norito;Sugawara, Akiyoshi
    • Journal of Computational Design and Engineering
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    • 제1권3호
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    • pp.202-212
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    • 2014
  • To survive in the current shipbuilding industry, it is of vital importance for shipyards to have the ship components' accuracy evaluated efficiently during most of the manufacturing steps. Evaluating components' accuracy by comparing each component's point cloud data scanned by laser scanners and the ship's design data formatted in CAD cannot be processed efficiently when (1) extract components from point cloud data include irregular obstacles endogenously, or when (2) registration of the two data sets have no clear direction setting. This paper presents reformative point cloud data processing methods to solve these problems. K-d tree construction of the point cloud data fastens a neighbor searching of each point. Region growing method performed on the neighbor points of the seed point extracts the continuous part of the component, while curved surface fitting and B-spline curved line fitting at the edge of the continuous part recognize the neighbor domains of the same component divided by obstacles' shadows. The ICP (Iterative Closest Point) algorithm conducts a registration of the two sets of data after the proper registration's direction is decided by principal component analysis. By experiments conducted at the shipyard, 200 curved shell plates are extracted from the scanned point cloud data, and registrations are conducted between them and the designed CAD data using the proposed methods for an accuracy evaluation. Results show that the methods proposed in this paper support the accuracy evaluation targeted point cloud data processing efficiently in practice.

수간석해(樹幹析解) 전산(電算)프로그램 개발(開發) 및 생장량(生長量) 계산방법(計算方法)의 비교(比較)에 관(關)한 연구(硏究) (A Development of Stem Analysis Program and its Comparison with other Method for Increment Calculation)

  • 변우혁;이우균;윤광배
    • 한국산림과학회지
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    • 제79권1호
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    • pp.1-15
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    • 1990
  • 본 연구에서는 수간석해의 분석시간과 경비를 줄이고 정확도를 높히기 위하여 P.C용 수간석해 프로그램을 제작하였으며, 본 프로그램에 이용된 수간석해 방법과 기존방법을 비교하여 다음과 같은 결과를 얻었다. 연륜측정기로 부터 1/100mm단위로 연륜 1개씩 측정된 data가 컴퓨터에 자동입력되도록 Turbo pascal을 이용하여 프로그램 하였다. 또한 각 단판의 직경이 단면적 평균법에 의해 계산되며, Spline function에 의해 재적 및 수고가 계산되도록 Fortran 77을 이용하여 수간석해 계산프로그램을 제작하였다. 이와같이 계산된 각종 생장량은 1년, 5년 단위로 각각 출력되며 수간석해도 및 각종 생장량도가 personal computer용 dot printer로 출력가능하여 수간 석해의 결과를 보다 쉽게 이용할 수 있게 되었다. 본 프로그램에서 이용된 수간석해 계산방법과 기존방법을 비교한 결과 단면적평균법이 편심에 의한 오차를 줄일 수 있었고, 수고 및 재적계산에서 Spline함수에 의한 간곡선 추정을 이용할 경우에는 다른 함수식에 의한 생장량 계산값보다 더욱 정확히 계산 가능하였다.

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소나무재선충병 감염목의 분광반사 특성 구명 (Investigation Into Reflectance Characteristics of Trees Infected by Pine Wilt Disease)

  • 김소라;이우균;남기준;송용호;유항남;김문일;이종열;이승호
    • 한국산림과학회지
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    • 제102권4호
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    • pp.499-505
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    • 2013
  • 소나무재선충병(Bursaphelenchus xylophilus)은 한국, 일본, 그리고 중국과 같은 동아시아의 소나무류 산림에 심각한 피해를 유발시킨다. 재선충병에 의한 병해는 그 치료방법이 훈증, 소각외에는 거의 없기 때문에 감염목을 조기 탐지하여 그 피해가 주변 임목 및 임분에 확산되지 않도록 하는 것이 최선책이라 할 수 있다. 본 연구에서는 소나무재선충병 감염목과 비감염목의 분광반사율을 주기적으로 측정하여 감염목의 분광반사 특성을 구명하였다. 이를 위하여, 6월에서 10월까지 GER3700 spectroradiometer를 이용하여 감염목과 비감염목의 400 nm~2,500 nm 파장대의 분광반사값을 측정하였다. 측정된 값의 noise를 보정하기 위하여 cubic spline 보간법을 사용하였다. 그 결과, 대부분의 감염목들은 재선충 주입 후 2개월 이내에 적색(600 nm~700 nm) 그리고 중적외선(1,400 nm~1,500 nm) 파장대에서 분광반사값의 변화를 보였으나, 비감염목들의 분광반사값은 어느 파장대에서도 특별한 변화가 나타나지 않았다. 시기별로 감염목과 비감염목의 분광반사값 변화를 통계적으로 비교해 본 결과, 소나무재선충 주입 2달 후 적색 파장대역과 중적외선 파장대역에서 가장 빠르게 통계적으로 유의한 차이를 보였으나(p<0.05), 근적외선 파장대역에서는 통계적으로 유의한 차이가 나타나지 않았다(p>0.05). 따라서 적색과 중적외선 파장대역에서의 분광반사율 변화를 통해 소나무재선충병 감염목의 조기 탐지가 가능한 것으로 판단되었다.

데이터 마이닝에서의 폴리클라스 (Polyclass in Data Mining)

  • 구자용;박헌진;최대우
    • 응용통계연구
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    • 제13권2호
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    • pp.489-503
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    • 2000
  • 다양한 형태의 데이터로부터 의사 결정에 유용한 정보 및 지식을 발견하려는 일련의 데이터분석 및 모형 선정과정을 데이터 마이닝(Data Mining)이라고 할 수 있다. 데이터 마이닝의 적용 예로는 신규고객에 대한 신용평가, 고객이탈방지 등과 같은 분야에서 발생하는 스코링 문제를 들 수 있는데 신용평가에서는 신용이 나쁠 가능성을 스코어로 나타내고 스코어가 높은 고객을 대상으로 특별관리를 할 수 있을 것이며 고객이탈방지에서는 이탈가능성을 스코어로 나타내고 스코어가 높은 고객을 대상으로 이탈 방지 캠페인을 벌일 수 있을 것이다. 본 논문에서는 스코링 문제를 사후확률에 대한 모형화 문제로 파악하였다. 폴리클라스를 스코링 문제에 적용하는 방법을 소개한 후 이를 독일 신용 데이터, 국내 모 PC통신회사 데이터 및 국내 모 이동통신 데이터에 적용하였다. 스코링의 성능은 이득률을 이용하여 평가하고자 하는데 나무 모형에 비하여 폴리클라스 방법이 우수함을 확인하였다.

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Bond strength prediction of spliced GFRP bars in concrete beams using soft computing methods

  • Shahri, Saeed Farahi;Mousavi, Seyed Roohollah
    • Computers and Concrete
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    • 제27권4호
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    • pp.305-317
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    • 2021
  • The bond between the concrete and bar is a main factor affecting the performance of the reinforced concrete (RC) members, and since the steel corrosion reduces the bond strength, studying the bond behavior of concrete and GFRP bars is quite necessary. In this research, a database including 112 concrete beam test specimens reinforced with spliced GFRP bars in the splitting failure mode has been collected and used to estimate the concrete-GFRP bar bond strength. This paper aims to accurately estimate the bond strength of spliced GFRP bars in concrete beams by applying three soft computing models including multivariate adaptive regression spline (MARS), Kriging, and M5 model tree. Since the selection of regularization parameters greatly affects the fitting of MARS, Kriging, and M5 models, the regularization parameters have been so optimized as to maximize the training data convergence coefficient. Three hybrid model coupling soft computing methods and genetic algorithm is proposed to automatically perform the trial and error process for finding appropriate modeling regularization parameters. Results have shown that proposed models have significantly increased the prediction accuracy compared to previous models. The proposed MARS, Kriging, and M5 models have improved the convergence coefficient by about 65, 63 and 49%, respectively, compared to the best previous model.