• Proceedings of the Korea Water Resources Association Conference
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• 2006.05a
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• pp.858-863
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• 2006

본 연구에서는 금강유역을 대상으로 GIS기법에 의해 1:5,000 NGIS자료로부터 DEM과 하천망을 생성하였고, 이를 이용하여 하천차수별 하천수, 하천연장과 평균하천연장의 하천특성인자와 유역면적, 유역평균폭, 최원유로연장, 하천총수, 총하천연장, 수계밀도, 수계빈도, 형상인자, 평균표고, 평균경사, 최대하천차수, 유역내 최고표고, 기복비 등의 유역특성인자들을 추출함으로써 수자원단위지도 기반의 단위유역별 지형학적 특성을 파악하였다. 또한 대상유역을 금강권역상류, 금강권역중류, 금강권역하류유역으로 구분하여 지형학적 인자를 추출하고 그 특성을 분석하였으며, 선형 및 비선형 회귀곡선을 이용하여 인자들 간의 상관관계를 분석함으로써 각 유역을 특징짓는 주요 인자들을 추출하였다.

• Journal of the military operations research society of Korea
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• v.36 no.2
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• pp.143-152
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• 2010

Military Power is the most direct and actual measures for national security. For construction, maintenance, management of military power, the adequate expenditure is required but it is difficult to increase blindly owing to the lack of resources. There are security threats and economic conditions in determining of military expenditure. Republic of Korea has been more influenced by economic conditions than by security threats since 1990s In this paper, we analysed relation between real military expenditure and real GDP through regression analysis.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2006.06a
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• pp.195-202
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• 2006

본 연구에서는 보다 효과적인 기업부도예측을 위하여, 동계적 방법과 인공지능 방법을 결합한 통합모형을 제시하였다. 이를 위하여 통계적인 모형 중에서 가장 널리 활용되고 있는 다변량 판별분석, 로지스틱 회귀분석과 인공 지능적인 방법으로서 최근 널리 사용되고 있는 인공신경망, 규칙유도기법, 베이지안 망의 5가지 방법론을 통합한 Voting with Performance & Weights from ANN(WP-ANN) 통합모형을 제시하였다. 실험결과, 본 연구에서 제안한 WP-ANN 통합모형은 다변량 판별분석, 로지스탁 회귀분석, 인공신경망, 규칙유도기법, 베이지안 망 등의 단일모형과 비교한 결과 가장 예측정확성이 유수한 것으로 나타났다. 따라서 본 연구를 통해 기업부도예측에 있어서 WP-ANN 통합모형이 기존의 모형들에 비해 우수한 예측정확성을 나타냄을 알 수 있었다.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.11
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• pp.809-814
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• 2013

Summed area table (SAT) is a data structure in which the sum of pixel values in an arbitrary rectangular area can be represented by the linear combination of four pixel values. Since SAT serially accumulates the pixel values from an image corner to the other corner, a high-resolution image can yield overflow in a floating-point representation. In this paper, we present a new SAT construction technique, which accumulates only the residuals from the linearly-regressed representation of an image and thereby significantly reduces the accumulation errors. Also, we propose a method to find the integral of the linear regression in constant time using double integral. We performed experiments on the image reconstruction, and the results showed that our approach more reduces the accumulation errors than the conventional fixed-offset SAT.

• Journal of Korean Society of Transportation
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• v.31 no.1
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• pp.65-76
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• 2013

Traffic accidents at signalized intersections have been increased annually so that it is required to examine the causation to reduce the accidents. However, the current existing accident models were developed mainly by using non-linear regression models such as Poisson methods. These non-linear regression methods lack to reveal the complicated causation for traffic accidents, though they are the right choice to study randomness and non-linearity of accidents. Therefore, it is required to utilize another statistical method to make up for the lack of the non-linear regression methods. This study developed accident prediction models for 4 legged signalized intersections with Poisson methods and compared them with structural equation models. This study used structural equation methods to reveal the complicated causation of traffic accidents, because the structural equation method has merits to explain more causational factors for accidents than others.

• Korean Journal of Food Science and Technology
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• v.28 no.5
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• pp.916-921
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• 1996

This study was conducted to measure fat contents of potatochips by near infrared spectroscopy (NIRS). Both potatochip powder and potatochips were used to find correlations between the absorbance at certain wavelengths find the fat contents. Based on the correlation analysis, linear regression models predicting the fat contents were developed to predict the fat contents. Artificial neural network (ANN) models were also developed. Predicted values were compared to the measured ones. The regression and the ANN model predicting the fat contents of potatochip powder had determination coefficients of 0.93 and 0.92, and standard errors of prediction (SEP) of 1.29% and 1.17%, respectively. The correlation analysis of potatochips showed that the determination coefficients were low. Therefore, the fat contents of not potatochips but potatochip powder could be measured by NIRS.

• Proceedings of the Korea Water Resources Association Conference
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• 2008.05a
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• pp.997-1000
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• 2008

기상 레이더와 지상강우계를 이용한 실시간 강우산정기법은 전형적인 Marshall-Palmer(M-P) 방법, geostatistic 접근법을 이용한 방법, 회귀분석에 의한 방법, Kalman filter를 이용한 방법 및 실시간 weight mask를 이용한 보정 등 여러 형태가 존재한다. 본 연구에서는 실시간 강우산정을 위한 각 방법의 장단점 및 적용성을 분석하였다. 전형적인 M-P 방법은 잘 알려진 바와 같이 호우사상을 과소 추정하는 단점을 가졌으며 기존 연구자들이 제시한 바와 같이 층운형, 대류형과 같은 강우형태에 따라 다른 Z-R관계식을 가지므로 단일 Z-R관계식으로 강수를 산정함에 있어 한계를 가진다. Geostatistic 기법을 이용한 실시간 강수 산정의 경우, 지상 강우계 정보를 활용하여 강우공간분포를 개선하는 여러 기법 즉 cokriging, external drift 기법 등이 존재함에도 불구하고 과다한 계산시간, 실시간 variogram 산정과 적용상의 문제 등을 내포하고 있다. 실시간 회귀분석을 이용한 강우산정은 실제 적용에 있어 지상 강우계와 레이더 반사도사이의 선형 상관관계에 대한 결정계수가 매우 낮아 기법 적용이 간단한 장점에도 불구하고 적용에 한계를 가진다. Kalman filter기법을 이용한 실시간 레이더 강수산정은 계산시간이 여타 기법보다 많이 소요되어 실시간성을 유지하는데 한계를 가진다. 실시간 weight mask를 이용한 보정기법은 지상강우계 강우강도와 기상레이더 강우강도가 선형상관관계를 가진다는 가정이 대상지역 전체에 균일하게 적용될 수 없음에도 불구하고 기법의 적용이 간편하며 실시간 강우 공간분포를 실제 강우 관측인 지상 강우계 공간 분포 특성을 간접 강우 관측인 기상 레이더 반사도 분포와 결합하여 공간 변화 특성을 잘 나타낸다는 장점을 가지므로 실용적 적용에 있어 장점을 가진다.

• Journal of Korea Water Resources Association
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• v.44 no.4
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• pp.275-283
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• 2011

A local or site-specific water temperature is downscaled from the nation-wide air temperature that represents simulation by General Circulation Model (GCM). Both two-step and one-step method are tested and compared in three sites: Masan Bay, Lake Sihwa, and Nakdong River Estuary. Two-step method uses a linear regression model as the first step that converts nation-wide air temperature into local air temperature, and the corresponding coefficient of determination is in the range of 0.98~0.99. The second step that converts air temperature into water temperature uses a nonlinear curve, so called S-curve, and the corresponding root mean squared error (RMSE) is 2.07 for rising limb in Masan Bay, 1.93 for falling limb in Masan Bay, 2.59 for Lake Sihwa, and 1.58 for Nakdong River Estuary. In a similar way, one-step method is performed to directly convert nation-wade air temperature into local water temperature, and the corresponding RMSE is 2.28 for rising limb in Masan Bay, 1.89 for falling limb in Masan Bay, 2.55 for Lake Sihwa, and 1.52 for Nakdong River Estuary. Consequently both methods show a similar level of performance, and one-step method is recommendable in that it is simple and practical in relative terms.

• Journal of the Korea Society of Computer and Information
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• v.25 no.3
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• pp.109-115
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• 2020

In this paper, we propose an artificial intelligence(AI) technology analysis using partial least square(PLS) regression model. AI technology is now affecting most areas of our society. So, it is necessary to understand this technology. To analyze the AI technology, we collect the patent documents related to AI from the patent databases in the world. We extract AI technology keywords from the patent documents by text mining techniques. In addition, we analyze the AI keyword data by PLS regression model. This regression model is based on the technique of partial least squares used in the advanced analyses such as bioinformatics, social science, and engineering. To show the performance of our proposed method, we make experiments using AI patent documents, and we illustrate how our research can be applied to real problems. This paper is applicable not only to AI technology but also to other technological fields. This also contributes to understanding other various technologies by PLS regression analysis.

• The Korean Journal of Applied Statistics
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• v.13 no.2
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• pp.437-445
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• 2000

The present paper is introducing a new model so called TAR-GARCH in the context of stock price analysis Conventional models such as AR(l), TAR(l), ARCH(I) and GARCH( 1,1) are briefly reviewed and TAR-GARCH is suggested in analyizing domestic stock prices. Also, relevant iterative estimation procedure is developed. It is seen that TAR-GARCH provides the better fit relative to traditional first order models for stock prices data in Korea.