• Title/Summary/Keyword: Prediction Analysis

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동적인장하중시 무기력상수에 의한 수명 예측 (Life Prediction by Lethargy Coefficient under Dynamic Load)

  • Kwon, S.J.;Song, J.H.;Kang, H.Y.;Yang, S.M.
    • 한국정밀공학회지
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    • 제14권7호
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    • pp.91-98
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    • 1997
  • Because of a complicated behavior of fatigue in mechanical structures, the analysis of fatigue is in need of much researches on life prediction. A method is developed for the dynamic tensile strength analysis by simple tensile test, which is for the failure life prediction by lethargy coefficient of various materials. Then it is programed to analyze the failure life prediction of mechanical system by virtue of fracture. Thus the dynamic tensile strength analysis is performed to evaluate life parameters as a numerical example, using the developed method.

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인공신경망을 이용한 기업도산 예측 - IMF후 국내 상장회사를 중심으로 - (A Neural Network Model for Bankruptcy Prediction -Domestic KSE listed Bankrupted Companies after the foreign exchange crisis in 1997)

  • 정유석;이현수;채영일;서영호
    • 한국품질경영학회:학술대회논문집
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    • 한국품질경영학회 2004년도 품질경영모델을 통한 가치 창출
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    • pp.655-673
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    • 2004
  • This paper is concerned with analysing the bankruptcy prediction power of three models: Multivariate Discriminant Analysis(MDA ), Logit Analysis, Neural Network. The after-crisis bankrupted companies were limited to the research data and the listed companies belonging to manufacturing industry was limited to the research data so as to improve prediction accuracy and validity of the model. In order to assure meaningful bankruptcy prediction, training data and testing data were not extracted within the corresponding period. The result is that prediction accuracy of neural network model is more excellent than that of logit analysis and MDA model when considering that execution of testing data was followed by execution of training data.

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A PROFIRABILITY MODEL BASED ON PRIMARY FACTOR ANALYSIS IN THE EARLY PHASE OF HOUSING REDEVELOPMENT PROJECTS

  • Kyeong-Hwan Ahn;U-Yeong Gim;Jong-Sik Lee;Won Kwon;Jae-Youl Chun
    • 국제학술발표논문집
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    • The 5th International Conference on Construction Engineering and Project Management
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    • pp.497-501
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    • 2013
  • An important decision-making element for the success of housing redevelopment projects is a prediction of the profitability of redevelopment. Risk factors influencing profitability were deduced through a review of the literature about profitability and a risk analysis developed by a survey of maintenance projects. In addition, a profitability prediction depending on the analysis of risk factors is necessary to judge the business feasibility of a project in the planning stages. A profitability prediction model of management and disposal method, which is calculated by proportional rate and which helps estimate contributions to profitability, is proposed to prevent difficulties in business development. The proposed model has the potential to prevent interruptions, reduce the length of projects, generate cost savings, and enable rational decision-making during the project period by allowing a judgment of profitability at the planning stage.

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불량탄 안전사고 예방을 위한 탄약 수명 예측 연구 리뷰 (A Review on Ammunition Shelf-life Prediction Research for Preventing Accidents Caused by Defective Ammunition)

  • 정영진;홍지수;김솔잎;강성우
    • 대한안전경영과학회지
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    • 제26권1호
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    • pp.39-44
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    • 2024
  • In order to prevent accidents via defective ammunition, this paper analyzes recent research on ammunition life prediction methodology. This workanalyzes current shelf-life prediction approaches by comparing the pros and cons of physical modeling, accelerated testing, and statistical analysis-based prediction techniques. Physical modeling-based prediction demonstrates its usefulness in understanding the physical properties and interactions of ammunition. Accelerated testing-based prediction is useful in quickly verifying the reliability and safety of ammunition. Additionally, statistical analysis-based prediction is emphasized for its ability to make decisions based on data. This paper aims to contribute to the early detection of defective ammunition by analyzing ammunition life prediction methodology hereby reducing defective ammunition accidents. In order to prepare not only Korean domestic war situation but also the international affairs from Eastern Europe and Mid East countries, it is very important to enhance the stability of organizations using ammunition and reduce costs of potential accidents.

수막두께와 속도를 고려한 도로포장면의 미끄럼저항 예측모델 개발 (A Development of Skid Resistance Prediction Model Considering Water Film Thickness and Vehicle Speed)

  • 조신행;이수형;유인균;김낙석
    • 대한토목학회논문집
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    • 제32권3D호
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    • pp.223-229
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    • 2012
  • 도로 포장면과 타이어 사이의 마찰 저항을 미끄럼 저항이라고 한다. 미끄럼 저항은 도로 안전에 매우 중요한 요소이며, 다양한 요인이 복합적으로 작용한다. 미끄럼 저항 측정법의 한계를 극복하기 위해 컴퓨터 모델링을 이용한 해석 수행 결과, 속도가 증가하거나 수막두께가 두꺼울수록 미끄럼 저항은 감소하였다. 해석 결과를 이용해 수막두께와 속도에 따라 수막 위를 주행하는 타이어에 발생하는 양력을 계산할 수 있으며, IFI(International Friction Index) 미끄럼 저항 예측모델과 실측 미끄럼 저항과의 차이를 줄이기 위해 양력을 반영한 수정 IFI 미끄럼 저항 예측모델을 개발하였다. 예측모델과 실측 데이터의 상관관계 분석 결과, 기존 IFI 예측모델의 $R^2$는 0.49로, 수정 IFI 예측모델의 $R^2$는 0.64로 나타나 수정 IFI 예측모델이 기존모델에 비해 예측 효과가 우수하였다. 포장면의 상태에 따른 수막두께를 수정 예측모델에 반영할 경우 더욱 정확한 예측모델을 얻을 수 있을 것이다.

평 블록 구조의 용접변형 예측 및 제어 (Prediction and Control of Welding Deformation for Panel Block Structure)

  • 김상일
    • 한국해양공학회지
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    • 제22권6호
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    • pp.95-99
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    • 2008
  • The block assembly of ship consists of a certain type of heat processes such as cutting, bending welding residual stress relaxation and fairing. The residual deformation due to welding is inevitable at each assembly stage. The geometric inaccuracy caused by the welding deformation tends to preclude the introduction of automation and mechanization and needs the additional man-hours for the adjusting work at the following assembly stage. To overcome this problem, a distortion control method should be applied. For this purpose, it is necessary to develop an accurate prediction method which can explicitly account for the influence of various factors on the welding deformation. The validity of the prediction method must be also clarified through experiments. This paper proposes a simplified analysis method to predict the welding deformation of panel block structure. For this purpose, a simple prediction model for fillet welding deformations has been derived based on numerical and experimental results through the regression analysis. On the basis of these results, the simplified analysis method has been applied to some examples to show its validity.

설계 민감도 해석을 활용한 진동내구 예측방법 연구 (Vibration fatigue prediction using design sensitivity analysis)

  • 김찬중;주형준;신성영;권성진;이봉현
    • 한국소음진동공학회:학술대회논문집
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    • 한국소음진동공학회 2011년도 추계학술대회 논문집
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    • pp.488-493
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    • 2011
  • Authors previously suggested the design sensitivity analysis based on transmissibility function and identified the sensitivity of measured point over the small modification of system dynamics. On the other hand, the acceleration data will not reveal the strain information at the same location and authors suggested energy isoclines that successfully predict the fatigue damage on the interesting location to overcome the drawback of acceleration over fatigue society. Both of methodologies, sensitivity analysis and fatigue damage prediction, commonly use the response acceleration response as main indicator. In this paper, authors investigate the advanced method of vibration fatigue prediction using design sensitivity analysis to enhance the accuracy of predicted accumulated fatigue. Uni-axial vibration testing is performed with finite element model of a simple notched specimen and the prediction of fatigue damage at notched location is conducted for accelerations at different measurement locations that show different sensitivity contribution, either.

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Influencing factors and prediction of carbon dioxide emissions using factor analysis and optimized least squares support vector machine

  • Wei, Siwei;Wang, Ting;Li, Yanbin
    • Environmental Engineering Research
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    • 제22권2호
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    • pp.175-185
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    • 2017
  • As the energy and environmental problems are increasingly severe, researches about carbon dioxide emissions has aroused widespread concern. The accurate prediction of carbon dioxide emissions is essential for carbon emissions controlling. In this paper, we analyze the relationship between carbon dioxide emissions and influencing factors in a comprehensive way through correlation analysis and regression analysis, achieving the effective screening of key factors from 16 preliminary selected factors including GDP, total population, total energy consumption, power generation, steel production coal consumption, private owned automobile quantity, etc. Then fruit fly algorithm is used to optimize the parameters of least squares support vector machine. And the optimized model is used for prediction, overcoming the blindness of parameter selection in least squares support vector machine and maximizing the training speed and global searching ability accordingly. The results show that the prediction accuracy of carbon dioxide emissions is improved effectively. Besides, we conclude economic and environmental policy implications on the basis of analysis and calculation.

입도분석에 기반한 Deep Neural Network를 이용한 최대 건조 단위중량 예측 모델 평가 (Evaluation of Maximum Dry Unit Weight Prediction Model Using Deep Neural Network Based on Particle Size Analysis)

  • 김명환
    • 한국농공학회논문집
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    • 제65권3호
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    • pp.15-28
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    • 2023
  • The compaction properties of the soil change depending on the physical properties, and are also affected by crushing of the particles. Since the particle size distribution of soil affects the engineering properties of the soil, it is necessary to analyze the material properties to understand the compaction characteristics. In this study, the size of each sieve was classified into four in the particle size analysis as a material property, and the compaction characteristics were evaluated by multiple regression and maximum dry unit weight. As a result of maximum dry unit weight prediction, multiple regression analysis showed R2 of 0.70 or more, and DNN analysis showed R2 of 0.80 or more. The reliability of the prediction result analyzed by DNN was evaluated higher than that of multiple regression, and the analysis result of DNN-T showed improved prediction results by 1.87% than DNN. The prediction of maximum dry unit weight using particle size distribution seems to be applied to evaluate the compacting state by identifying the material characteristics of roads and embankments. In addition, the particle size distribution can be used as a parameter for predicting maximum dry unit weight, and it is expected to be of great help in terms of time and cost of applying it to the compaction state evaluation.

A Hilbert-Huang Transform Approach Combined with PCA for Predicting a Time Series

  • Park, Min-Jeong
    • 응용통계연구
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    • 제24권6호
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    • pp.995-1006
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    • 2011
  • A time series can be decomposed into simple components with a multiscale method. Empirical mode decomposition(EMD) is a recently invented multiscale method in Huang et al. (1998). It is natural to apply a classical prediction method such a vector autoregressive(AR) model to the obtained simple components instead of the original time series; in addition, a prediction procedure combining a classical prediction model to EMD and Hilbert spectrum is proposed in Kim et al. (2008). In this paper, we suggest to adopt principal component analysis(PCA) to the prediction procedure that enables the efficient selection of input variables among obtained components by EMD. We discuss the utility of adopting PCA in the prediction procedure based on EMD and Hilbert spectrum and analyze the daily worm account data by the proposed PCA adopted prediction method.