• Communications for Statistical Applications and Methods
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• v.11 no.3
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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.

• Korean Journal of Computational Design and Engineering
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• v.15 no.1
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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.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.12
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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.

• Journal of the Korean Wood Science and Technology
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• v.50 no.2
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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.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.13 no.3
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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.

• Journal of Computational Design and Engineering
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• v.1 no.3
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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.

• Journal of Korean Society of Forest Science
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• v.79 no.1
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• pp.1-15
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• 1990

In this study the stem analysis program, which can be operated with personal computer was developed to reduce time and cost of calculation, and to increase accuracy of analysis. The stem analysis method used in this program was compared with other methods. The results obtained were as follows : The value, 1/100mm measured from the latest annual ring measurement machine (Jahrringme${\beta}$geraete Johan Type II) was automatically inputed to the computer and saved into given file name. Turbo Pascal program was written to do this. The measured data was analyzed by stem analysis calculation program written by Fortran-77. Volume and height increments were approximated by spline function, and diameter of the stem disk was calculated by quadratic mean method. The increment values calculated by the programs were printed annually and in every five-year. Stem analysis diagram and several increment graphs were also easily printed. The result compared between those analysis methods showed that quadratic mean could reduce the error caused from eccentric pith. When the stem taper curve method, approximated by spline function, was used in the calculation of tree height and volume, increments would be more exactly calculated.

• Journal of Korean Society of Forest Science
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• v.102 no.4
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• pp.499-505
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• 2013

Pine wilt disease has known as a serious forest disease in East Asia such as Japan, Korea and China. Fumigation and burning are considered as best way to treat infected tree at early detection. For investigate spectral reflectance characteristics of infected trees, periodic measurement has been done in both infected and non-infected trees. Infected and non-infected trees' reflectance (400 nm~2,500 nm wavelength) are detected from June to October with GER3700 spectrometer. Noise of reflectance data was corrected using cubic spline interpolation method. Reflectance was changed in most of infected trees with ranges Red (600 nm~700 nm) and Middle Infrared (1,400 nm~1,500 nm) within two months after injected by Pine Wood nematode (PWN), but there was no differences in non-infected trees. Infected and non-infected trees were compared statistically in each period. As a result, we found that a statistically significant difference was occurred at Red and Middle Infrared (MIR) 2 months after injection (p<0.05), however, no significant difference in near infrared (p>0.05). Therefore, the early detection of infested pine trees by PWN may possible through detecting the change of spectral reflectance at red and MIR.

• The Korean Journal of Applied Statistics
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• v.13 no.2
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• pp.489-503
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• 2000

Data mining means data analysis and model selection using various types of data in order to explore useful information and knowledge for making decisions. Examples of data mining include scoring for credit analysis of a new customer and scoring for churn management, where the customers with high scores are given special attention. In this paper, scoring is interpreted as a modeling process of the conditional probability and polyclass scoring method is described. German credit data, a PC communication company data and a mobile communication company data are used to compare the performance of polyclass scoring method with that of the scoring method based on a tree model.

• Computers and Concrete
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• v.27 no.4
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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.