• Journal of the Korea Institute of Military Science and Technology
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• v.16 no.5
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• pp.675-682
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• 2013

Reliability analysis and prediction of next failure time is critical to sustain weapon systems, concerning scheduled maintenance, spare parts replacement and maintenance interventions, etc. Since 1981, many methodology derived from various probabilistic and statistical theories has been suggested to do that activity. Nowadays, many A.I. tools have been used to support these predictions. Support Vector Regression(SVR) is a nonlinear regression technique extended from support vector machine. SVR can fit data flexibly and it has a wide variety of applications. This paper utilizes SVM and SVR with combining time series to predict the next failure time based on historical failure data. A numerical case using failure data from the military equipment is presented to demonstrate the performance of the proposed approach. Finally, the proposed approach is proved meaningful to predict next failure point and to estimate instantaneous failure rate and MTBF.

• 도로교통
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• s.94
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• pp.51-64
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• 2003

본 연구는 사고요인과 사고모형의 문헌고찰을 통해 고속도로를 주행하는 버스와 화물차의 사고모형을 개발하고 그 적용방안에 대해 고찰하고자 수행되었다. 고속도로 사고 중 대형차로 인한 차량당 사고율은 승용차보다 월등히 높아 사고의 심각성을 나타내고 있으며, 따라서 이에 대한 별도의 검토가 필요한 시점에 와 있다. 특히 본 연구에 활용된 자료는 비집계된 사상자수로 구간자료를 집합화함으로써 발생하는 문제점을 해소할 수 있다. 모형의 분석기법으로 국내의 경우, 대부분 단순회귀식으로 사고모형을 개발, 적용하여 왔으나 사고수와 사상자수의 특성상 이산적 확률변수로 해석하여 포아송분포와 음이항분포로 적용하는 것이 바람직하다. 따라서 본 연구에서는 버스와 화물차의 사고유형별로 적합한 사고 모형을 개발하여 이로 인한 인사사고 요인에 대한 영향을 분석하고 그 적용방안을 제시하였다. 이러한 연구는 도로설계, 운영, 교통법규, 교통행정 등의 분야에서 거시적인 정책적 방향성을 제시하리라 판단된다. 특히 본 연구는 고속도로 운영주체인 한국도로공사의 고속도로사고조서를 바탕으로 사고유형별 사고모형을 개발, 적용한 것으로 고속도로의 안정성 향상을 위한 제반 정책 수립에 기초자료로 활용될 것으로 기대된다.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.12 no.12
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• pp.1090-1097
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• 2000

Predicting building energy use can be useful to evaluate its energy performance. This study proposed empirical approach for predicting building energy use with regression analysis. For the empirical analysis, simple regression models were developed based on the historical energy consumption data as a function of daily outside temperature, the predicting equations were derived for different operational modes and day types, then the equations were applied for predicting energy use in a building. BY selecting a real building as a case study, the feasibilities of the empirical approach for predicting building energy use were examined. The results showed that empirical approach with regression analysis was fairly reliable by demonstrating prediction accuracy of $pm10%$ compared with the actual energy consumption data. It was also verified that the prediction by regression models could be simple and fairly accurate. Thus, it is anticipated that the empirical approach will be useful and reliable tool for many purposes: retrofit savings analysis by estimating energy usage in an existing building or the diagnosis of the building operational problems with real time analysis.

• The Korean Journal of Financial Studies
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• v.2 no.1
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• pp.71-100
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• 1995

금융서비스 분야의 급속한 개방압력하에서 국내은행들은 영업환경의 급변으로 심각한 경영위기에 봉착함에 따라서 어느 때 보다 경쟁력 확보가 급선무가 되었다. 장기적으로는 대형화와 전문화, 전문인력 양성 둥을 통한 경쟁력 확보도 중요하겠지만 우선적으로 과학적인 경영효율성 측정을 통한 은행내부의 비효율원인을 규명하고 문제점을 개선하는 것이 중요할 것이다. 본 연구에서는 시중은행의 각 영업점 경영효율성의 측정방법간의 특성과 문제점을 찾고, 최근에 비영리기관의 경영효율성에 주로 이용되는 BEA기법을 적용하여 비효율의 원인을 규명하는데 중점을 두었다. 연구결과 은행 영업점의 규모를 지나치게 영세하게 운영함으로서 규모의 효율성을 이루지 못하였고, 주로 은행에서 경영성과측정수단으로 이용하고 있는 비율분석이나 회귀분석을 개별적으로 사용하는 것보다는 DEA기법을 병행 사용함으로서 측정상의 오류를 개선할 수 있음을 보여주었다. 또한 비율분석의 규명과 최적 생산규모점을 찾는데 DEA기법의 유용성을 제시하였다.

• The Korean Journal of Applied Statistics
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• v.27 no.4
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• pp.629-643
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• 2014

It is common to check the validity of an assumed model with the heavy use of diagnostics tools when conducting data analysis with regression techniques; however, outliers and influential data points often distort the regression output in undesired manner. Jang and Anderson-Cook (2013) proposed a graphical method called a firework plot for exploratory analysis that could visualize the trace of the impact of possible outlying and/or influential data points on individual regression coefficients and the overall residual sum of squares(SSE) measure. They developed 3-D plot as well as pair-wise plot for the appropriate measures of interest. In this paper, the approach was extended further to tell the strength of their approach; in addition, a more meaningful interpretation was possible by adding a measure not mentioned in their paper. This approach was applied to the mixture experiment because we felt that a detailed analysis of statistical measure sensitivity is required in a small experiment.

• Journal of the Korean Association of Geographic Information Studies
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• v.11 no.4
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• pp.193-202
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• 2008

The objectives of this study are to analyze the spatial site characteristics of existing tombs and the change in the pattern of spatial distributions of tombs over time. The spatial distributions of tombs located in Honam province along the Honam expressway were investigated by interpreting digital aerial photographs taken in two different points of time; 1990 and 2000. According to the results of the study, the tombs newly observed in 2000 photos were located closer to roads and villages than those found in the photos of 1990. This is a finding indicating that the accessibility of tombs has been more important consideration in determining the location of tomb sites. Also found were the gentle slopes of southern aspects to be favored as tomb sites. Based on the data sets of tombs locations and their topographic site characteristics, the probability function of tombs appearance in the study area was derived using the logistic regression analysis technique. As a result, tomb sites were classified as 74.7% by logistic regression. All of six input factors (elevation, slope, aspect, distance from the roads, the town and the stream, respectively) affected the probability of tombs appearance significantly.

• Journal of Korean Society of Transportation
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• v.27 no.3
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• pp.81-90
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• 2009

The safety management of a road network comprises four basic inter-related components：identification of sites(black spot) requiring safety investigation, diagnosis of safety problems, selection of feasible treatments for potential treatment candidates, and prioritization of treatments given limited budgets(Persaud, 2001). Identification process of selecting black spot is very important for efficient investigation of sites. In this study, the accident prediction model for EB method was developed by using accident data and geometric conditions of black spots selected from four-leg signalized intersections in In-cheon City for three years (2004-2006). In addition, by comparing the rank nomination technique using EB method to that by using accident counts, we managed to show the problems which the existing method have and the necessity for developing rational prediction model. As a result, in terms of total number of accidents, both the counts predicted by existing non-linear regression model and that by EB method have high good of fitness, but EB method, considering both the accident counts by sites and total number of accident, has better good of fitness than non-linear poison model. According to the result of the comparison of ranks nominated for treatment between two methods, the rank for treatment of almost sites does not change but SeoHae intersection and a few other intersections have significant changes in their rank. This shows that, with the technique proposed in the study, the RTM problem caused by using real accident counts can be overcome.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.29-29
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• 2018

전 세계적으로 홍수, 태풍, 폭설 등 기상이변에 따른 자연재난이 빈번히 발생하고 있으며, 국내의 경우 연간 약 5천억원 이상의 피해가 발생하고 있다. 미국 및 일본 등의 방재 선진국의 경우 재난 발생 전에 대비하는 재난관리가 중심을 이루고 있으며, 국내에서도 피해가 발생하기 전에 신속하게 재난피해를 예측 및 대비한다면 인명과 재산피해를 최소화 할 수 있을 것이라 판단된다. 따라서 본 연구에서는 신속하게 재난 피해를 예측하기 위해 기존에 함수 개발시 활발하게 사용되었던 다중회귀분석과 최근 이슈가 되고 있는 머신러닝(기계학습)을 활용하여 호우로 인한 피해를 사전에 예측하는 함수를 개발하였다. 행정안전부에서 구축하고 있는 재해연보 자료를 종속변수로 활용하였고, 기상요소 및 사회 경제적 요소를 설명변수로 사용하였다. 본 연구에서 개발된 호우피해 예측함수를 이용하여 호우피해를 예측하고, 이를 기반으로 사전 대비 차원의 재난관리를 실시한다면 자연재난으로 인한 피해를 줄이는데 큰 도움이 될 것으로 판단된다.

• The Korean Journal of Applied Statistics
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• v.24 no.5
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• pp.951-961
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• 2011

In this paper, we propose a Bayesian inference using the Markov Chain Monte Carlo(MCMC) method for the zero inflated negative binomial(ZINB) regression model. The proposed model allows the regression model for zero inflation probability as well as the regression model for the mean of the dependent variable. This extends the work of Jang et al. (2010) to the fully defiend ZINB regression model. In addition, we apply the proposed method to a real data example, and compare the efficiency with the zero inflated Poisson model using the DIC. Since the DIC of the ZINB is smaller than that of the ZIP, the ZINB model shows superior performance over the ZIP model in zero inflated count data with overdispersion.

• 한국ITS학회:학술대회논문집
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• 2003.11a
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• pp.221-225
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• 2003