• 한국도로학회논문집
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• 제18권3호
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• pp.109-114
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• 2016

PURPOSES : The demand for extending national highways is increasing, but traffic monitoring is hindered because of resource limitations. Hence, this study classified highway segments into 5 types to improve the efficiency of short-term traffic count planning. METHODS : The traffic volume trends of 880 highway segments were classified through R-squared and linear regression analyses; the steadiness of traffic volume trends was evaluated through coefficient of variance (COV), and the normality of the data were determined through the Shapiro-Wilk W-test. RESULTS : Of the 880 segments, 574 segments had relatively low COV and were classified as type 1 segments, and 123 and 64 segments with increasing and decreasing traffic volume trends were classified as type 2 and type 3 segments, respectively; 80 segments that failed the normality test were classified as type 4, and the remaining 39 were classified as type 5 segments. CONCLUSIONS : A theoretical basis for biennial count planning was established. Biennial count is recommended for types 1~4 because their mean absolute percentage errors (MAPEs) are approximately 10%. For type 5 (MAPE =19.26%), the conventional annual count can be continued. The results of this analysis can reduce the traffic monitoring budget.

• 한국통계학회:학술대회논문집
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• 한국통계학회 2005년도 춘계 학술발표회 논문집
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• pp.277-283
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• 2005

주식가격은 일반적으로 정규분포를 따르지 않으며 이러한 비정규성을 띤 주식의 매매전략은 일반적으로 추세 지표, 변동성 지표, 거래량 지표 등을 토대로 수립되며 통계적이기 보다는 직관적이라고 볼 수 있다. 주식가격의 비정규성 문제는 주식가격의 정규화 과정을 통해서 해결 될 수 있으며 통계적인 매매전략은 정규화된 주식가격의 평균추세 지표 및 변동성 지표를 결합하여 작성될 수 있다. 본 논문은 정규화된 주식가격의 평균추세 지표와 변동성 지표를 결합한 매매전략을 제시하였고 이를 KOSPI200에 적용한 결과 성공적인 매매전략이 될 수 있는 가능성을 확인하였다.

• 대한산업공학회지
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• 제26권3호
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• pp.193-199
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• 2000

In many studies, considerable attention has been focussed upon choosing a model which represents underlying process of time series and forecasting the future. In the real world, however, there may be some cases that one model can not reflect all the characteristics of original time series. Under such circumstances, we may get better performance by combining the forecasts from several models. The most popular methods for combining forecasts involve taking a weighted average of multiple forecasts. But the weights are usually unstable. In cases the assumptions of normality and unbiasedness for forecast errors are satisfied, a Bayesian method can be used for updating the weights. In the real world, however, there are many circumstances the Bayesian method is not appropriate. This paper proposes a PNN(Probabilistic Neural Net) approach as a method for combining forecasts that can be applied when the assumption of normality or unbiasedness for forecast errors is not satisfied. In this paper, PNN method, which is similar to Bayesian approach, is suggested as an updating method of the unstable weights in the combination of the forecasts. The PNN method has been usually used in the field of pattern recognition. Unlike the Bayesian approach, it requires no assumption of a specific prior distribution because it gets probabilities by using the distribution estimated from given data. Empirical results reveal that the PNN method offers superior predictive capabilities.

• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2019년도 추계 학술논문 발표대회
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• pp.207-208
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• 2019

Currently, as the public interest for environmental issues has grown rapidly, the needs for G-SEED have also increased. However, as investment according to eco-friendly elements is inevitable to receive G-SEED certification, it is necessary to find out whether or not the sales price of apartments have increased compared to investment costs. Therefore, the objective of this study is to analyze the sales price of apartments according to G-SEED by using T-test. To achieve the objective, First, variables affecting on the sales price of apartments are selected. Second, the data are collected by using GIS(Geographic Information System). Third, after testing the normality, a comparison analysis is conducted on the sales price between G-SEED certified and non-certified apartments by using T-test. As a result, it is concluded that G-SEED certified apartments are more expensive than non-certified apartments. In the future, these findings can be utilized to develop of apartments price calculation model based on the G-SEED.

• 한국컴퓨터정보학회논문지
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• 제27권6호
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• pp.167-174
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• 2022

본 논문에서는 여러 개의 독립적인 모집단들 사이에서 상관계수들의 등가성에 대한 퍼뮤테이션 검정을 조사한다. 퍼뮤테이션 검정은 관측값들의 상호교환성에 기초하는 비모수적인 검정 방법이며 상호교환성이란 독립적이고 동일한 확률변수들의 개념을 일반화한 개념이다. 퍼뮤테이션 검정을 사용함으로써 근사적으로 정확한 검정에 가까운 검정을 실시할 수 있다. 퍼뮤테이션 검정은 근사적으로 보수적인 검정만큼의 검정력을 지니며, 표본의 크기가 작거나 정규성 가정이 충족되지 않을 때 유용한 방법이다. 본 논문에서는 먼저 상관계수들의 등가성을 검정하는 모수적인 방법들을 소개하고 이들을 퍼뮤테이션 검정과 비교한다. 끝으로 모든 검정들은 Iris 데이터를 예를 들어 비교된다.

• Journal of Animal Science and Technology
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• 제63권2호
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• pp.440-452
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• 2021

The purpose of this study was to determine if an 8-week therapeutic riding (TR) program was effective in improving the walking ability of students with intellectual disabilities. Thirteen students diagnosed with intellectual disabilities participated in the TR program. TR sessions were conducted twice a week (30 min per session), with a total of 16 rides taking place over an 8-week period. A gait measurement analyzer was used to measure progress based on a turn test (6-m walking and turning test), walk test (10-m walking), and timed up and go (TUG) test. Measurements were made three times: before horse-riding (P0), after 4 weeks (8 rides) of horse-riding (P1), and after 8 weeks (16 rides) of horse-riding (P2). Data analysis was conducted using SPSS software (ver. 22.0). Descriptive statistics were generated on the general characteristics of the subjects, and the Kolmogorov-Smirnov test was used to verify the normality of the data. Because of the lack of normality, the data were analyzed using a nonparametric method and the significance level was set to 0.05. Measurements of the duration of the forward gait cycle (s) in the turn test and the forward gait speed (m/s) in the walk test indicated improved walking ability after the TR program (p < 0.001); the stride length (% height) also increased significantly (p < 0.05). The walk test revealed a significant effect of the program on the duration of the forward gait cycle (p < 0.05), while there were significant improvements on the left and right of the elaborated strides (p < 0.001). No significant improvement in TUG test performance was observed after the TR program. In this study, an 8-week TR program had positive results on gait. Therefore, further research is merited, where TR programs are likely to improve the walking ability of individuals with intellectual disabilities.

• 한국컴퓨터정보학회논문지
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• 제23권3호
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• pp.63-70
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• 2018

In this work, we analyze the relationship between the accumulated mileage of hybrid electric vehicle(HEV) and the data provided from vehicle parts. Data were collected while traveling over 70,000 Km in various paths. The data collected in seconds are aggregated for 10 minutes and characterized in terms of centrality, variability, normality, and so on. We examined whether the statistical properties of vehicle parts are different for each cumulative mileage interval of a hybrid car. When the cumulative mileage interval is categorized into =< 30,000, <= 50,000, and >50,000, the statistical properties are classified by the mileage interval as 82.3% accuracy. This indicates that if the data of the vehicle parts is collected by operating the hybrid vehicle for 10 minutes, the cumulative mileage interval of the vehicle can be estimated. This makes it possible to detect the abnormality of the vehicle part relative to the accumulated mileage. It can be used to detect abnormal aging of vehicle parts and to inform maintenance necessity.

• International Journal of Internet, Broadcasting and Communication
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• 제14권4호
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• pp.140-147
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• 2022

In this study, in order to efficiently detect data patterns and outliers in time series data, outlier detection processing is performed for each section based on a smart contract in the data preprocessing process, and parameters for the ARIMA model are determined by generating and reflecting the significance and outlier-related parameters of the data. It was created and applied to the modified arithmetic expression to lower the data abnormality. To evaluate the performance of this study, the normality of the data was compared and evaluated when the parameters of the general ARIMA model and the ARIMA model through this study were applied, and a performance improvement of more than 6% was confirmed.

• Journal of the Korean Data and Information Science Society
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• 제18권4호
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• pp.1005-1021
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• 2007

Traditional procedures for DNA microarray data analysis are to preprocess and normalize the gene expression data, and then to analyze the normalized data using statistical tests. Drawbacks of the traditional methods are: genuine biological signal may be unwillingly eliminated together with artifacts, the limited number of arrays per gene make statistical tests difficult to use the normality assumption or nonparametric method, and genes are tested independently without consideration of interrelationships among genes. A novel method using average rank in each array is proposed to eliminate such drawbacks. This average rank method monitors differentially regulated genes among genetically different groups and the selected genes are somewhat different from those selected by traditional P-value method. Addition of genes selected by the average rank method to the traditional method will provide better understanding of genetic differences of groups.

• 한국통계학회:학술대회논문집
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• 한국통계학회 2002년도 춘계 학술발표회 논문집
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• pp.67-72
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• 2002

A Bayesian testing procedure is proposed for assessment of bioequivalence in both mean and variance which ensures population bioequivalence under normality assumption. We derive the joint posterior distribution of the means and variances in a standard 2 ${\times}$ 2 crossover experimental design and propose a Bayesian testing procedure for bioequivalence based on a Markov chain Monte Carlo methods. The proposed method is applied to a real data set.