• 제목/요약/키워드: Cross - Validation

검색결과 994건 처리시간 0.034초

어머니용 부모공동양육 척도 개발 및 타당화 연구 (The Development and Validation of a Coparenting Scale for Mother (CS-M))

  • 전선영;이희선
    • 한국보육지원학회지
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    • 제18권3호
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    • pp.37-59
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    • 2022
  • Objective: The purpose of this study is to develop and validate a coparenting scales(mother's version) suitable for the Korean situation. Methods: In this study, mothers with one or more children were targeted. First, factor structure and construct validity were verified(N=412), and second, cross-validation and concurrent validity were verified(N=312). Results: The coparenting scale(mother's version) is largely composed of the mother's own coparenting and their spouse's coparenting. First, as a result of performing an exploratory factor analysis, three factors were extracted from the mother's own coparenting and their spouse's coparenting, and they were labeled parenting cooperation, parenting agreement, and parenting sharing. Through confirmatory factor analysis, 13 items were identified with three factors. Second, cross-validation was performed on a new group with confirmatory factor analysis, and as a result, validity was secured by satisfying the model validation criteria. In addition, the correlation between the existing scale and parenting efficacy was significant, thus securing concurrent validity. Conclusion/Implications: Through this study, the coparenting scale(mother's version) that was developed may provide practical guidelines for family coparenting by identifying mothers' perceptions of coparenting, and can be used in parent education and child-rearing policies.

A Study on the Land Cover Classification and Cross Validation of AI-based Aerial Photograph

  • Lee, Seong-Hyeok;Myeong, Soojeong;Yoon, Donghyeon;Lee, Moung-Jin
    • 대한원격탐사학회지
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    • 제38권4호
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    • pp.395-409
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    • 2022
  • The purpose of this study is to evaluate the classification performance and applicability when land cover datasets constructed for AI training are cross validation to other areas. For study areas, Gyeongsang-do and Jeolla-do in South Korea were selected as cross validation areas, and training datasets were obtained from AI-Hub. The obtained datasets were applied to the U-Net algorithm, a semantic segmentation algorithm, for each region, and the accuracy was evaluated by applying them to the same and other test areas. There was a difference of about 13-15% in overall classification accuracy between the same and other areas. For rice field, fields and buildings, higher accuracy was shown in the Jeolla-do test areas. For roads, higher accuracy was shown in the Gyeongsang-do test areas. In terms of the difference in accuracy by weight, the result of applying the weights of Gyeongsang-do showed high accuracy for forests, while that of applying the weights of Jeolla-do showed high accuracy for dry fields. The result of land cover classification, it was found that there is a difference in classification performance of existing datasets depending on area. When constructing land cover map for AI training, it is expected that higher quality datasets can be constructed by reflecting the characteristics of various areas. This study is highly scalable from two perspectives. First, it is to apply satellite images to AI study and to the field of land cover. Second, it is expanded based on satellite images and it is possible to use a large scale area and difficult to access.

스태킹 앙상블 기법을 활용한 고속도로 교통정보 예측모델 개발 및 교차검증에 따른 성능 비교 (Development of Highway Traffic Information Prediction Models Using the Stacking Ensemble Technique Based on Cross-validation)

  • 이요셉;오석진;김예진;박성호;윤일수
    • 한국ITS학회 논문지
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    • 제22권6호
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    • pp.1-16
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    • 2023
  • 정확도가 높은 교통정보 예측은 지능형교통체계(intelligent transport systems, ITS)를 통한 교통 시설 이용자들의 혼잡 경로 회피 안내 등에서 활용되는 중요한 기능이다. 정확한 교통정보예측을 위해 다양한 딥러닝 모델들이 발전되어 왔다. 최근에는 앙상블 기법을 활용하여 다양한 모델들의 장단점을 결합하여 예측 정확도와 안정성을 높이고 있다. 따라서, 본 연구에서는 다양한 딥러닝 모델들을 활용하여 교통정보 예측 모델을 개발하였으며, 개발된 딥러닝 모델들을 스태킹 앙상블(stacking ensemble)하여 성능을 개선하였다. 개별 모델들은 교통량 예측에서 10% 이내의 오차율을, 속도 예측에서 3% 이내의 오차율을 보였다. 앙상블 모델은 교차검증을 수행하지 않았을 때, 타 모델과 비교하여 더욱 높은 정확도를 보였다. 교차검증을 수행한 앙상블 모델은 장기예측에서 타 모델보다 균일한 오차율을 보이는 것으로 나타났다.

스마트 기기 환경에서 전력 신호 분석을 통한 프라이버시 침해 위협 (Threatening privacy by identifying appliances and the pattern of the usage from electric signal data)

  • 조재연;윤지원
    • 정보보호학회논문지
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    • 제25권5호
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    • pp.1001-1009
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    • 2015
  • 스마트 그리드 안에서 고안된 스마트 미터는 우리가 사용하는 전력 신호를 실시간으로 데이터화해서 전력 공급단의 메인 서버로 전송한다. 이를 통해 전력 관리의 효율성은 증가한 반면, 사용자의 정보를 담은 데이터의 보안 문제가 새로운 위협으로 부상하였다. 본 논문은 스마트 미터에서 추출한 전력 데이터를 통해 가정 내 기기의 식별 및 기기별 사용패턴에 대한 추론을 보안 관점에서 해석함으로써 스마트 기기 환경에서 데이터 노출의 위협을 지적한다. 주성분분석(Principal Component Analysis)으로 데이터의 특징을 추출하였고 k-근접 이웃(k- Nearest Neighbor)분류기로 기기를 식별하고 기기상태를 추론하였으며, 검증방법으로는 10차 교차검증(10-fold Cross Validation)을 활용하였다.

항공기 날개의 통계적 중량 예측식 도출 연구 (A Study on Deriving the Statistical Weight Estimation Formula for an Aircraft Wing)

  • 김석범;정한규;황호연
    • 한국항공우주학회지
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    • 제46권1호
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    • pp.32-40
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    • 2018
  • 본 논문에서는 개념설계 단계에서 주로 사용되는 통계적 중량 예측식 도출 방법에 관한 연구를 수행하였으며 Microsoft Excel을 이용해 이를 프로그램화하고 제트 여객기에 적용하여 검증하였다. 기존 중량 예측식들의 변수들을 참고하여 데이터베이스를 구축하였고 이를 사용하여 제트 여객기 날개 중량 예측식을 모델링하였다. 모델의 과적합 문제를 해결하기 위해 K-fold cross validation 방법을 사용하여 모델을 평가하였다.

평균제곱오차를 이용한 크리깅 근사모델의 오차 평가 (An Error Assessment of the Kriging Based Approximation Model Using a Mean Square Error)

  • 주병현;조태민;정도현;이병채
    • 대한기계학회논문집A
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    • 제30권8호
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    • pp.923-930
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    • 2006
  • A Kriging model is a sort of approximation model and used as a deterministic model of a computationally expensive analysis or simulation. Although it has various advantages, it is difficult to assess the accuracy of the approximated model. It is generally known that a mean square error (MSE) obtained from the kriging model can't calculate statistically exact error bounds contrary to a response surface method, and a cross validation is mainly used. But the cross validation also has many uncertainties. Moreover, the cross validation can't be used when a maximum error is required in the given region. For solving this problem, we first proposed a modified mean square error which can consider relative errors. Using the modified mean square error, we developed the strategy of adding a new sample to the place that the MSE has the maximum when the MSE is used for the assessment of the kriging model. Finally, we offer guidelines for the use of the MSE which is obtained from the kriging model. Four test problems show that the proposed strategy is a proper method which can assess the accuracy of the kriging model. Based on the results of four test problems, a convergence coefficient of 0.01 is recommended for an exact function approximation.

IRF-k kriging of electrical resistivity data for estimating the extent of saltwater intrusion in a coastal aquifer system

  • Shim B. O.;Chung S. Y.;Kim H. J.;Sung I. H.
    • 한국지구물리탐사학회:학술대회논문집
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    • 한국지구물리탐사학회 2003년도 Proceedings of the international symposium on the fusion technology
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    • pp.352-361
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    • 2003
  • We have evaluated the extent of saltwater intrusion from electrical resistivity distribution in a coastal aquifer system in the southeastern part of Busan, Korea. This aquifer system is divided into four layers according to the hydrogeologic characteristics and the horizontal extent of intruded saltwater is determined at each layer through the geostatistical interpretation of electrical resistivity data. In order to define the statistical structure of electrical resistivity data, variogram analysis is carried out to obtain best generalized covariance models. IRF-k (intrinsic random function of order k) kriging is performed with covariance models to produce the plane of spatial mean resistivities. The kriged estimates are evaluated by cross validation to show a good agreement with the true values and the statistics of cross validation represented low errors for the estimates. In the resistivity contour maps more than 5 m below the surface, we can see a dominant direction of saltwater intrusion beginning from the east side. The area of saltwater intrusion increases with depth. The northeast side has low resistivities less than 5 ohm-m due to the presence of saline water in the depth range of 20 m through 70 m. These results show that the application of geostatistical technique to electrical resistivity data is useful for assessing saltwater intrusion in a coastal aquifer system.

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호흡곤란 환자 퇴원 결정을 위한 벌점 로지스틱 회귀모형 (Penalized logistic regression models for determining the discharge of dyspnea patients)

  • 박철용;계묘진
    • Journal of the Korean Data and Information Science Society
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    • 제24권1호
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    • pp.125-133
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    • 2013
  • 이 논문에서는 호흡곤란을 주호소로 내원한 668명의 환자를 대상으로 11개 혈액검사 결과를 이용하여 퇴원여부를 결정하는 벌점 이항 로지스틱 회귀 기반 통계모형을 유도하였다. 구체적으로 $L^2$ 벌점에 근거한 능형 모형과 $L^1$ 벌점에 근거한 라소 모형을 고려하였다. 이 모형의 예측력 비교 대상으로는 일반 로지스틱 회귀의 11개 전체 변수를 사용한 모형과 변수선택된 모형이 사용되었다. 10-묶음 교차타당성 (10-fold cross-validation) 비교 결과 능형 모형의 예측력이 우수한 것으로 나타났다.

Estimating the Natural Cubic Spline Volatilities of the ASEAN-5 Exchange Rates

  • LAIPAPORN, Jetsada;TONGKUMCHUM, Phattrawan
    • The Journal of Asian Finance, Economics and Business
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    • 제8권3호
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    • pp.1-10
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    • 2021
  • This study examines the dynamic pattern of the exchange rate volatilities of the ASEAN-5 currencies from January 2006 to August 2020. The exchange rates applied in this study comprise bilateral and effective exchange rates in order to investigate the influence of the US dollar on the stability of the ASEAN-5 currencies. Since a volatility model employed in this study is a natural cubic spline volatility model, the Monte Carlo simulation is consequently conducted to determine an appropriate criterion to select a number of quantile knots for this model. The simulation results reveal that, among four candidate criteria, Generalized Cross-Validation is a suitable criterion for modeling the ASEAN-5 exchange rate volatilities. The estimated volatilities showed the inconstant dynamic patterns reflecting the uncertain exchange rate risk arising in international transactions. The bilateral exchange rate volatilities of the ASEAN-5 currencies to the US dollar are more variable than their corresponding effective exchange rate volatilities, indicating the influence of the US dollar on the stability of the ASEAN-5 currencies. The findings of this study suggest that the natural cubic spline volatility model with the quantile knots selected by Generalized Cross-Validation is practical and can be used to examine the dynamic patterns of the financial volatility.