• 제목/요약/키워드: Field data analysis

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RAM 분석 정확도 향상을 위한 야전운용 데이터의 이상값과 결측값 처리 방안 (Method of Processing the Outliers and Missing Values of Field Data to Improve RAM Analysis Accuracy)

  • 김인석;정원
    • 한국신뢰성학회지:신뢰성응용연구
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    • 제17권3호
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    • pp.264-271
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    • 2017
  • Purpose: Field operation data contains missing values or outliers due to various causes of the data collection process, so caution is required when utilizing RAM analysis results by field operation data. The purpose of this study is to present a method to minimize the RAM analysis error of the field data to improve the accuracy. Methods: Statistical methods are presented for processing of the outliers and the missing values of the field operating data, and after analyzing the RAM, the differences between before and after applying the technique are discussed. Results: The availability is estimated to be lower by 6.8 to 23.5% than that before processing, and it is judged that the processing of the missing values and outliers greatly affect the RAM analysis result. Conclusion: RAM analysis of OO weapon system was performed and suggestions for improvement of RAM analysis were presented through comparison with the new and current method. Data analysis results without appropriate treatment of error values may result in incorrect conclusions leading to inappropriate decisions and actions.

A Big Data-Driven Business Data Analysis System: Applications of Artificial Intelligence Techniques in Problem Solving

  • Donggeun Kim;Sangjin Kim;Juyong Ko;Jai Woo Lee
    • 한국빅데이터학회지
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    • 제8권1호
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    • pp.35-47
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    • 2023
  • It is crucial to develop effective and efficient big data analytics methods for problem-solving in the field of business in order to improve the performance of data analytics and reduce costs and risks in the analysis of customer data. In this study, a big data-driven data analysis system using artificial intelligence techniques is designed to increase the accuracy of big data analytics along with the rapid growth of the field of data science. We present a key direction for big data analysis systems through missing value imputation, outlier detection, feature extraction, utilization of explainable artificial intelligence techniques, and exploratory data analysis. Our objective is not only to develop big data analysis techniques with complex structures of business data but also to bridge the gap between the theoretical ideas in artificial intelligence methods and the analysis of real-world data in the field of business.

한국형 재해평가모형(RAM)의 초기입력자료 적합성 평가 (Compatibility for the Typhoon Damages Predicted by Korea Risk Assessment Model Input Data)

  • 박종길;이보람;정우식
    • 한국환경과학회지
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    • 제24권7호
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    • pp.865-874
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    • 2015
  • This study was conducted to investigate the correlation between the distribution chart and input data of the predicted 3-second gust and damage cost, by using the forecast field and analysis field of Regional Data Assimilation Prediction System (RDAPS) as initial input data of Korea risk assessment model (RAM) developed in the preceding study. In this study the cases of typhoon Rusa which caused occurred great damage to the Korean peninsula was analyzed to assess the suitability of initial input data. As a result, this study has found out that the distribution chart from the forecast field and analysis field predicted from the point where the effect due to the typhoon began had similarity in both 3-second gust and damage cost with the course of time. As a result of examining the correlation, the 3-second gust had over 0.8, and it means that the forecast field and analysis field show similar results. This study has shown that utilizing the forecast field as initial input data of Korea RAM could suit the purpose of pre-disaster prevention.

초탄성 복합재의 평균장 균질화 데이터 기반 멀티스케일 해석 (A Data-driven Multiscale Analysis for Hyperelastic Composite Materials Based on the Mean-field Homogenization Method)

  • 김수한;이원주;신현성
    • Composites Research
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    • 제36권5호
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    • pp.329-334
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    • 2023
  • 기존의 멀티스케일 유한요소법(Multiscale finite element, FE2 )은 거시 스케일의 모든 적분점에서 대표 체적요소(representative volume element, RVE)의 미시 경계치 문제를 반복적으로 계산하기 때문에 긴 해석 시간과 많은 데이터 저장 공간을 필요로 한다. 이를 해결하기 위해 본 연구에서 평균장 균질화 데이터 기반 멀티스케일 해석 기법을 개발하였다. 데이터 기반 전산역학(data-driven computational mechanics, DDCM) 해석은 변형률-응력 데이터 셋을 직접적으로 사용하는 모델-프리(model-free)접근 방식이다. 멀티스케일 해석을 수행하기 위해, 평균장 균질화(mean-field homogenization)를 활용하여 복합재의 미세구조에 대한 변형률-응력 데이터베이스(database)를 효율적으로 구축하고, 이를 기반으로 데이터 기반 전산역학 시뮬레이션을 수행하였다. 본 논문에서는 개발한 멀티 스케일 해석 프레임워크(framework)를 예제에 적용하여, 초탄성(hyperelasticity) 복합재의 미세 구조를 고려한 데이터 기반 전산역학 시뮬레이션 결과를 확인하였다. 따라서, 데이터 기반 전산역학 접근 방식을 활용한 멀티스케일 해석기법은 다양한 재료 및 구조에 적용될 수 있으며, 멀티스케일 해석 연구 및 응용 가능성을 열어줄 것으로 기대된다.

시공 단계를 고려한 터널의 역해석에 관한 연구 (Back Analysis of Tunnel for multi-step Construction)

  • 김선명;윤지선
    • 한국지반공학회:학술대회논문집
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    • 한국지반공학회 2000년도 가을 학술발표회 논문집
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    • pp.479-484
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    • 2000
  • The reliable estimation of the system parameters and the accurate prediction of the system behavior are important to design tunnel safely and economically. Therefore, the back analysis using the field measurements data is useful to evaluate the geotechnical parameter for tunnel. In the back analysis method, the selection of initial value and uncertainty of field measurements influence significantly on the analysis result. In this paper, to overcome uncertainty of field measurements, we performed the back analysis using the displacement data gained at each step of excavation and support.

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차량부품 문제에 대한 실험계획법과 Field Data 분석을 통한 신뢰성 평가연구 (Research of Reliability Assessment through the Analysis of Field Data and Taguchi Method about Vehicle Components Problem)

  • 강창학;유재복;이치우;김장수
    • 한국산업융합학회 논문집
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    • 제13권4호
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    • pp.211-217
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    • 2010
  • As the vehicle components are various, we confront unexpected problems in the development and application of them. also warranty expenses occur in the result of unconfirmed warranty.in this paper, to solve the problems of disconnection of damper Strut cable, we applied the optimum conditions through taguchi method for improvement of durability. and we made standard of reliability by weibull analysis of the field data. we acquired reliability standard by correlation with lab data and confirmed improved components satisfying the target of reliability. The analysis of reliability by field data is very useful and we need to apply this method to other components, the correlation between field data and Lab Test has influence on satisfying the target of reliability.this method would be utilized for current mass production components and upcoming developed components. the reliability of durability should be continuously used in the basis of primary technique in cope with competitive automotive companies.

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자동차 필드데이터 수집 및 신뢰도 분석 (Collection and Analysis of Automotive Field Reliability Data)

  • 권영인
    • 한국신뢰성학회지:신뢰성응용연구
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    • 제8권1호
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    • pp.1-13
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    • 2008
  • A methodology for collection and analysis of automotive field reliability data is presented. Automotive warranty system usually covers a pre-determined period of time and/or mileage accumulation. Therefore mileage information for the vehicles that have not experienced any failure or problems during the warranty period is not available. In this paper, a reliability analysis method using the estimated mileage distribution from an additional survey for vehicles that have not any record during the warranty period is proposed. Methods of reliability analysis using the warranty information collected under the EU and US warranty policies are also provided.

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야전 운용자료를 이용한 비 모수 통계 기반의 신뢰도 분석 기법 및 활용 방안 연구 (A Research of the Reliability Analysis and Application Method Based on Non-parametric Statistics Using Field Data)

  • 나일용
    • 한국군사과학기술학회지
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    • 제13권4호
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    • pp.594-600
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    • 2010
  • In this paper, we introduced non-parametric statisticals method that could analyse the field data and proposed application ways such as repair-part demand forcasting, MTBF estimation and trend analysis, identity comparison with two populations using the analytical results. In addition, we applied that to real field data which has been collected for about ten years from K series tracked vehicle. After that, we compared the results with those using traditional parametric statistical method, and verified the usability of them.

Pressure equalization of rainscreen facades: Analysis of the field data in the frequency domain

  • Kumar, K. Suresh;Wisse, J.A.
    • Wind and Structures
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    • 제4권2호
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    • pp.101-118
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    • 2001
  • This paper reports the field measurements concerning pressure equalization of rainscreen facades carried out at the Technical University of Eindhoven (TUE) in the Netherlands. The field facility including the details of test panel, meteorological tower, instrumentation, data collection and analysis is presented. Results of investigations into cavity response for various leakage and venting configurations are discussed. Frequency domain techniques have been utilized to show the influence of wind as well as facade characteristics on the pressure equalization performance. Further, this paper presents an early attempt to synthesize the experimental results into existing building codes.

전기철도 차량에 대한 극저주파 자계영역의 시간영역 측정 및 스펙트럼 분석 (Time-domain measurement and spectral analysis of low frequency magnetic field on board of rolling stock)

  • 장동욱;정상기
    • 한국철도학회:학술대회논문집
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    • 한국철도학회 2008년도 추계학술대회 논문집
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    • pp.263-268
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    • 2008
  • The measurement of magnetic field is performed AC magnetic field emission density in driver cab and saloon's compartment of rolling stock. In order to measure magnetic-field emission, a three-axial magnetic-field sensor is used and connected to data process system. The AC magnetic field is checked and analysis through BNC output, DAQ cad and notebook PC. The spectral analysis is performed by short time Fourier transform(STFT) for time-domain emission signal.

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