• 제목/요약/키워드: Empirical Method

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신호교차로 안전성향상을 위한 단속카메라의 효과분석 연구 -측면직각 충돌사고를 중심으로- (Effect Analysis on Red Light Camera for Signalized Intersection Safety -Focused on Side Right-Angle Collision Accidents-)

  • 오주택;김용석;이용철
    • 한국도로학회논문집
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    • 제17권1호
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    • pp.119-127
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    • 2015
  • PURPOSES : Before-and-after studies of red light cameras were conducted with the aim of reducing the number of side right-angle collisions. Three different methods were used for the before-and-after studies, and the analysis results were compared. METHODS : This research used the naive before-and-after method, the comparison-group method, and the empirical Bayes method to study the effects of red light cameras on side-angle collisions. The results of the three before-and-after methods were compared and interpreted in terms of safety indications at signalized intersections. RESULTS : The research results showed that side right-angle collisions can be reduced by installing red light cameras at signalized intersections. All three methods guarantee safety improvements of 25~30% on average. With regard to the results of each method, the naive before-and-after method, the comparison-group method, and the empirical Bayes method showed safety improvements of 25.6%, 27.8%, and 29.7%, respectively. CONCLUSIONS : It was concluded that red light cameras are an effective countermeasure to improve intersection safety. In particular, by installing red light cameras, side right-angle collisions can be reduced by up to approximately 25~30%.

Empirical Bayes Method를 이용한 교통사고 예측모형 (A Study on the Traffic Accident Estimation Model using Empirical Bayes Method)

  • 강현건;강승규;장용호
    • 대한교통학회지
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    • 제27권5호
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    • pp.135-144
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    • 2009
  • 본 연구는 경북도내에서 발생한 4년간의 교통사고 자료를 대상으로 Empirical Bayes (EB) 방법을 이용하여 예상사고건수를 예측하였다. 경북도내 각 군과 시 지역의 교통사고는 대물피해환산법을 적용하여 심각도를 반영하였으며, EB 방법을 적용하기 위해 군집분석을 통해 유사한 지역을 선정하였고, 선정된 유사지역을 대상으로각 지역별 안전성능함수(SPF)를 도출하였다. 실제 사고건수와의 근원적인 확률분포를 일치시키기 위해 과분산 파라메타를 산출하였으며, 지역별 교통특성을 반영하기 위해 가중치를 적용하여 예상 사고건수를 예측하였다. 분석 결과 김천시, 영천시, 칠곡군 순으로 가장 높은 사고건수가 예상되는 반면, 군위군이 가장 낮은 사고건수가 발생할 것으로 예측되었다.

Empirical Statistical Power for Testing Multilocus Genotypic Effects under Unbalanced Designs Using a Gibbs Sampler

  • Lee, Chae-Young
    • Asian-Australasian Journal of Animal Sciences
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    • 제25권11호
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    • pp.1511-1514
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    • 2012
  • Epistasis that may explain a large portion of the phenotypic variation for complex economic traits of animals has been ignored in many genetic association studies. A Baysian method was introduced to draw inferences about multilocus genotypic effects based on their marginal posterior distributions by a Gibbs sampler. A simulation study was conducted to provide statistical powers under various unbalanced designs by using this method. Data were simulated by combined designs of number of loci, within genotype variance, and sample size in unbalanced designs with or without null combined genotype cells. Mean empirical statistical power was estimated for testing posterior mean estimate of combined genotype effect. A practical example for obtaining empirical statistical power estimates with a given sample size was provided under unbalanced designs. The empirical statistical powers would be useful for determining an optimal design when interactive associations of multiple loci with complex phenotypes were examined.

Efficiency and Returns to Scale in the Bangladesh Banking Sector: Empirical Evidence from the Slack-Based DEA Method

  • Sufian, Fadzlan;Kamarudin, Fakarudin
    • 아태비즈니스연구
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    • 제5권1호
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    • pp.1-11
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    • 2014
  • The study provides new empirical evidence on the level of profit efficiency and returns to scale of the Bangladesh banking sector. We employ the Slack-Based Data Envelopment Analysis (SBM-DEA) method to assess the level of profit efficiency of individual banks over the years 2004 to 2011. The empirical findings indicate that the Bangladesh banking sector has exhibited the highest and lowest level of profit efficiency during years 2004 and 2011 respectively. We find that only eight banks have been profit efficient throughout the period under study. The empirical findings seem to suggest that most of the Bangladesh banks have been experiencing economies of scale due to being at less than the optimum size, or diseconomies of scale due to being at more than the optimum size. Thus, decreasing or increasing the scale of production could result in cost savings or efficiencies.

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복합재 박막 구조물의 압축강도 예측 (Predicting the Compressive Strength of Thin-walled Composite Structure)

  • 김성준;이동건
    • 한국항공운항학회지
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    • 제27권2호
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    • pp.9-15
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    • 2019
  • The initial buckling of thin walled structures does not result in immediate failure. This post buckling capability is used to achieve light weight design, and final failure of thin walled structure is called crippling. To predict the failure load, empirical methods are often used for thin walled structures in design stage. But empirical method accuracy depend on geometry. In this study, experimental, empirical and numerical study of the crippling behavior of I-section beam made of carbon-epoxy are performed. The progressive failure analysis model to simulate the crippling failure is evaluated using the test results. In this study, commercial software LS-DYNA is utilized to compute the collapse load of composite specimen. Six kinds of specimens were tested in axial compression where correlation between analytical and experimental results has performed. From the results, we have partially conclude that the flange width-to-thickness ratio is found to influence the accuracy of empirical and numerical method.

강도설계용 풍하중 평가를 위한 재현기간과 기본풍속지도의 제안 (Proposal of Return Period and Basic Wind Speed Map to Estimate Wind Loads for Strength Design in Korea)

  • 하영철
    • 대한건축학회논문집:구조계
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    • 제34권2호
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    • pp.29-40
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    • 2018
  • Strength design wind loads for the wind resistance design of structures shall be evaluated by the product of wind loads calculated based on the basic wind speed with 100 years return period and the wind load factor 1.3 specified in the provisions of load combinations in Korean Building Code (KBC) 2016. It may be sure that the wind load factor 1.3 in KBC(2016) had not been determined by probabilistic method or empirical method using meteorological wind speed data in Korea. In this paper, wind load factors were evaluated by probabilistic method and empirical method. The annual maximum 10 minutes mean wind speed data at 69 meteorological stations during past 40 years from 1973 to 2012 were selected for this evaluation. From the comparison of the results of those two method, it can be found that the mean values of wind load factors calculated both probability based method and empirical based method were similar at all meteorological stations. When target level of reliability index is set up 2.5, the mean value of wind load factors for all regions should be presented about 1.35. When target level of reliability index is set up 3.0, wind load factor should be presented about 1.46. By using the relationship between importance factor(conversion factor for return period) and wind load factor, the return periods for strength design were estimated and expected wind speeds of all regions accounting for strength design were proposed. It can be found that return period to estimate wind loads for strength design should be 500 years and 800 years in according to target level of reliability index 2.5 and 3.0, respectively. The 500 years basic wind speed map for strength design was suggested and it can be used with a wind load factor 1.0.

경험 모드 분리법을 이용한 감쇠 진동 신호의 분석 (Analysis of Damped Vibration Signal Using Empirical Mode Decomposition Method)

  • 이인재;이종민;황요하;허건수
    • 한국소음진동공학회논문집
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    • 제15권2호
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    • pp.192-198
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    • 2005
  • Empirical mode decomposition(EMD) method has been recently proposed to analyze non-linear and non-stationary data. This method allows the decomposition of one-dimensional signals into intrinsic mode functions(IMFs) and is used to calculate a meaningful multi-component instantaneous frequency. In this paper, it is assumed that each mode of damped vibration signal could be well separated in the form of IMF by EMD. In this case, we can have a new powerful method to calculate natural frequencies and dampings from damped vibration signal which usually has multiple modes. This proposed method has been verified by both simulation and experiment. The results by EMD method whichhas used only output vibration data are almost identical to the results by FRF method which has used both input and output data, thereby proving usefulness and accuracy of the proposed method.

경험 모드 분석법을 이용한 감쇠 진동 신호의 분석 (Analysis of Damped Vibration Signal using Empirical Mode Decomposition Method)

  • 이인재;이종민;황요하;허건수
    • 한국소음진동공학회:학술대회논문집
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    • 한국소음진동공학회 2004년도 추계학술대회논문집
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    • pp.699-704
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    • 2004
  • Empirical mode decomposition(EMD) method has been recently proposed to analyze non-linear and non-stationary data. This method allows the decomposition of one-dimensional signals into intrinsic mode functions(IMFs) and is used to calculate a meaningful multi-component instantaneous frequency. In this paper, it is assumed that each mode of damped vibration signal could be well separated in the form of IMF by EMD. In this case, we can have a new powerful method to calculate natural frequencies and dampings from damped vibration signal which usually has multiple modes. This proposed method has been verified by both simulation and experiment. The result by EMD method which has used only output vibration data is almost identical to the result by FRF method which has used both input and output data, thereby proving usefulness and accuracy of the proposed method.

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회귀분석에 의한 건물에너지 사용량 예측기법에 관한 연구 (A Study for Predicting Building Energy Use with Regression Analysis)

  • 이승복
    • 설비공학논문집
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    • 제12권12호
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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.

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Prediction of squeezing phenomenon in tunneling projects: Application of Gaussian process regression

  • Mirzaeiabdolyousefi, Majid;Mahmoodzadeh, Arsalan;Ibrahim, Hawkar Hashim;Rashidi, Shima;Majeed, Mohammed Kamal;Mohammed, Adil Hussein
    • Geomechanics and Engineering
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    • 제30권1호
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    • pp.11-26
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    • 2022
  • One of the most important issues in tunneling, is the squeezing phenomenon. Squeezing can occur during excavation or after the construction of tunnels, which in both cases could lead to significant damages. Therefore, it is important to predict the squeezing and consider it in the early design stage of tunnel construction. Different empirical, semi-empirical and theoretical-analytical methods have been presented to determine the squeezing. Therefore, it is necessary to examine the ability of each of these methods and identify the best method among them. In this study, squeezing in a part of the Alborz service tunnel in Iran was estimated through a number of empirical, semi- empirical and theoretical-analytical methods. Among these methods, the most robust model was used to obtain a database including 300 data for training and 33 data for testing in order to develop a machine learning (ML) method. To this end, three ML models of Gaussian process regression (GPR), artificial neural network (ANN) and support vector regression (SVR) were trained and tested to propose a robust model to predict the squeezing phenomenon. A comparative analysis between the conventional and the ML methods utilized in this study showed that, the GPR model is the most robust model in the prediction of squeezing phenomenon. The sensitivity analysis of the input parameters using the mutual information test (MIT) method showed that, the most sensitive parameter on the squeezing phenomenon is the tangential strain (ε_θ^α) parameter with a sensitivity score of 2.18. Finally, the GPR model was recommended to predict the squeezing phenomenon in tunneling projects. This work's significance is that it can provide a good estimation of the squeezing phenomenon in tunneling projects, based on which geotechnical engineers can take the necessary actions to deal with it in the pre-construction designs.