• 제목/요약/키워드: interval estimation

검색결과 658건 처리시간 0.022초

우도구간 추정법에 의한 피로강도 데이터 평가법에 관한 연구 (A Study on Evaluation Method of Fatigue Strength Data Using Likelihood Interval Estimation Method)

  • 최창섭
    • 한국안전학회지
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    • 제10권2호
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    • pp.10-16
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    • 1995
  • In estimating the fatigue data, only the uniform safety rate has been applied so far However, since more reasonable design concepts such as machine structures or subsidiary materials will be required in the future, the importance of a statistical estimation method for fatigue data is being highlighted. With such basic conception in mind, this study was aimed at critically discussing the interval estimation method which has been applied using the classical statistics thus far It was conceived that this conventional method would result in the estimation of the unstable side from the viewpoint of the likelihood Interval estimation method. In this regard, this study aimed at estimating the fatigue strength through the likelihood interval estimation method comparing it with the conventional interval estimation method would result in the estimation of the unstable side from the viewpoint of the likelihood interval estimation method. One of the methods using the likelihood for estimation data is the Bayes method. Based on this theory, statistical estimations were positivly applied, and thereupon, the fatigue data were estimated.

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연대측정자료를 이용한 단층활동주기 산정 방법 (Method of Recurrence Interval Estimation for Fault Activity from Age Dating Data)

  • 최원학
    • 한국지진공학회:학술대회논문집
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    • 한국지진공학회 2001년도 춘계학술대회 논문집
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    • pp.74-80
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    • 2001
  • The estimation of recurrence interval for fault activity and earthquake is an important input parameter for seismic hazard assessment. In this study, the methods of recurrences interval estimation were reviewed and tentative calculation was performed for age dating data which have uncertainty. Age dating data come from previous studies of Ulsan fault system which is a well developed lineament in the southeastern part of korean Peninsula. Age dating for fault gouges, parent rocks, Quaternary sediments and veins were carried out by several researchers through various methods. Recurrence interval for fault activity was estimated on the basis of the age dating data of minor fault gouge and sediments during past 3Ma. The estimated recurrence interval was about 430-500 ka. Exact estimation of recurrence interval for fault activity need to compile more geological data and fault characteristics such as fault length, amount of displacement, slip rate and accurate fault movement age. In the future, the methods and results of fault recurrence interval estimation should be considered for establishing the criteria for domestic active fault definition.

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GMM-TS를 이용한 표적기동분석용 배치구간 및 초기상태 추정 기법 (Batch Time Interval and Initial State Estimation using GMM-TS for Target Motion Analysis)

  • 김우찬;송택렬
    • 제어로봇시스템학회논문지
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    • 제18권3호
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    • pp.285-294
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    • 2012
  • Using bearing measurement only, target motion state is not directly obtained so that TMA (Target Motion Analysis) is needed for this situation. TMA is a nonlinear estimation technique used in passive SONAR systems. Also it is the one of important techniques for underwater combat management systems. TMA can be divided to two parts: batch estimation and sequential estimation. It is preferable to use sequential estimation for reducing computational load as well as adaptively to target maneuvers, batch estimation is still required to attain target initial state vector for convergence of sequential estimation. Selection of batch time interval which depends on observability is critical in TMA performance. Batch estimation in general utilizes predetermined batch time interval. In this paper, we propose a new method called the BTIS (Batch Time Interval and Initial State Estimation). The proposed BTIS estimates target initial status and determines the batch time interval sequentially by using a bank of GMM-TS (Gaussian Mixture Measurement-Track Splitting) filters. The performance of the proposal method is verified by a Monte Carlo simulation study.

Efficient Anomaly Detection Through Confidence Interval Estimation Based on Time Series Analysis

  • Kim, Yeong-Ju;Jeong, Min-A
    • International journal of advanced smart convergence
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    • 제4권2호
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    • pp.46-53
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    • 2015
  • This paper suggests a method of real time confidence interval estimation to detect abnormal states of sensor data. For real time confidence interval estimation, the mean square errors of the exponential smoothing method and moving average method, two of the time series analysis method, were compared, and the moving average method with less errors was applied. When the sensor data passes the bounds of the confidence interval estimation, the administrator is notified through alarms. As the suggested method is for real time anomaly detection in a ship, an Android terminal was adopted for better communication between the wireless sensor network and users. For safe navigation, an administrator can make decisions promptly and accurately upon emergency situation in a ship by referring to the anomaly detection information through real time confidence interval estimation.

Estimation in the exponential distribution under progressive Type I interval censoring with semi-missing data

  • Shin, Hyejung;Lee, Kwangho
    • Journal of the Korean Data and Information Science Society
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    • 제23권6호
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    • pp.1271-1277
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    • 2012
  • In this paper, we propose an estimation method of the parameter in an exponential distribution based on a progressive Type I interval censored sample with semi-missing observation. The maximum likelihood estimator (MLE) of the parameter in the exponential distribution cannot be obtained explicitly because the intervals are not equal in length under the progressive Type I interval censored sample with semi-missing data. To obtain the MLE of the parameter for the sampling scheme, we propose a method by which progressive Type I interval censored sample with semi-missing data is converted to the progressive Type II interval censored sample. Consequently, the estimation procedures in the progressive Type II interval censored sample can be applied and we obtain the MLE of the parameter and survival function. It will be shown that the obtained estimators have good performance in terms of the mean square error (MSE) and mean integrated square error (MISE).

최적화된 Interval Type-2 FCM based RBFNN 구조 설계 : 모델링과 패턴분류기를 중심으로 (Structural design of Optimized Interval Type-2 FCM Based RBFNN : Focused on Modeling and Pattern Classifier)

  • 김은후;송찬석;오성권;김현기
    • 전기학회논문지
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    • 제66권4호
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    • pp.692-700
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    • 2017
  • In this paper, we propose the structural design of Interval Type-2 FCM based RBFNN. Proposed model consists of three modules such as condition, conclusion and inference parts. In the condition part, Interval Type-2 FCM clustering which is extended from FCM clustering is used. In the conclusion part, the parameter coefficients of the consequence part are estimated through LSE(Least Square Estimation) and WLSE(Weighted Least Square Estimation). In the inference part, final model outputs are acquired by fuzzy inference method from linear combination of both polynomial and activation level obtained through Interval Type-2 FCM and acquired activation level through Interval Type-2 FCM. Additionally, The several parameters for the proposed model are identified by using differential evolution. Final model outputs obtained through benchmark data are shown and also compared with other already studied models' performance. The proposed algorithm is performed by using Iris and Vehicle data for pattern classification. For the validation of regression problem modeling performance, modeling experiments are carried out by using MPG and Boston Housing data.

On Estimation of HPD Interval for the Generalized Variance Using a Weighted Monte Carlo Method

  • Kim, Hea-Jung
    • Communications for Statistical Applications and Methods
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    • 제9권2호
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    • pp.305-313
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    • 2002
  • Regarding to inference about a scalar measure of internal scatter of Ρ-variate normal population, this paper considers an interval estimation of the generalized variance, │$\Sigma$│. Due to complicate sampling distribution, fully parametric frequentist approach for the interval estimation is not available and thus Bayesian method is pursued to calculate the highest probability density (HPD) interval for the generalized variance. It is seen that the marginal posterior distribution of the generalized variance is intractable, and hence a weighted Monte Carlo method, a variant of Chen and Shao (1999) method, is developed to calculate the HPD interval of the generalized variance. Necessary theories involved in the method and computation are provided. Finally, a simulation study is given to illustrate and examine the proposed method.

통계적 신뢰구간 개념을 도입한 검지기 성능평가 (Detector Evaluation Scheme Including the Concept of Confidence Interval in Statistics)

  • 장진환;김병화
    • 한국ITS학회 논문지
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    • 제10권1호
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    • pp.67-75
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    • 2011
  • 본 논문은 기존의 단일값(점추정)으로 제시하던 검지기 성능평가 결과를 통계적 신뢰구간(구간추정)으로 제시하기 위한 검지기 성능평가 방안을 제시했다. 일반적으로 구간추정은 점추정에 비해 표본 통계의 더 많은 정보를 제공하기 때문에 기존 단일값으로 제시해 오던 검지기 성능평가 결과의 신뢰성을 향상시킬 수 있다. 방법론은 크게 표본 추출, 평가척도 분석, 평가결과 제시의 세 부분으로 나누어진다. 표본추출 방법에는 다양한 통계적 표본 추출 방법이 있지만 교통, 조도, 기상조건에 따라 변화하는 차량검지기 성능의 특성상 층화추출법이 통계적 신뢰구간 제시를 위한 가장 적합한 방법론으로 간주되었다. 또한 기존에 널리 사용된 검지기 성능평가 척도들의 특징을 면밀히 분석하여 평가자로 하여금 해당 검지자료에 적합한 평가척도를 선택할 수 있는 프로세스를 정립하였다. 마지막으로 평가기간 전체(예. 30분)와 개별분석 단위(예. 1분) 평가결과의 통계적 신뢰구간을 반영하기 위한 방법론을 제시했다. 본 연구는 기존 검지기 성능평가 결과의 단일값 제시로 인해 불가능 했던 신뢰구간 제시를 가능하게 함에 따라 검지기 성능평가 결과의 신뢰성을 향상시킬 수 있을 것으로 판단된다.

가설검정 및 구간추정에서 샘플크기 결정규칙의 고찰 및 유도 (Review and Derivation of Sample Size Determination for Hypothesis Testing and Interval Estimation)

  • 최성운
    • 대한안전경영과학회:학술대회논문집
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    • 대한안전경영과학회 2012년 추계학술대회
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    • pp.461-471
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    • 2012
  • Most useful statistical techniques in six sigma DMAIC are hypothesis testing and interval estimation. So this paper reviews and derives sample size formula by considering significance level, power of detectability and effect difference. The quality practioners can effectively interpret the practical and statistical significance with the rational sample sizing.

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저주파진동 해석을 위한 다구간 파라미터 추정 방법 (A Parameter Estimation Method of Multiple Time Interval for Low Frequency Oscillation Analysis)

  • 심관식;김상태;최준호;남해곤;안선주
    • 전기학회논문지
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    • 제63권7호
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    • pp.875-882
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    • 2014
  • In this paper, we propose a new parameter estimation method that can deal with the data of multiple time intervals simultaneously. If there are common modes in the multiple time intervals, it is possible to create a new polynomial by summing the coefficients of the prediction error polynomials of each time interval. By calculating the roots of the new polynomial, it is possible to estimate the common modes that exist in each time interval. The accuracy of the proposed parameter estimation method has been proven by using appropriate test signals.