• 한국컴퓨터정보학회논문지
• /
• 제23권3호
• /
• pp.63-70
• /
• 2018

In this work, we analyze the relationship between the accumulated mileage of hybrid electric vehicle(HEV) and the data provided from vehicle parts. Data were collected while traveling over 70,000 Km in various paths. The data collected in seconds are aggregated for 10 minutes and characterized in terms of centrality, variability, normality, and so on. We examined whether the statistical properties of vehicle parts are different for each cumulative mileage interval of a hybrid car. When the cumulative mileage interval is categorized into =< 30,000, <= 50,000, and >50,000, the statistical properties are classified by the mileage interval as 82.3% accuracy. This indicates that if the data of the vehicle parts is collected by operating the hybrid vehicle for 10 minutes, the cumulative mileage interval of the vehicle can be estimated. This makes it possible to detect the abnormality of the vehicle part relative to the accumulated mileage. It can be used to detect abnormal aging of vehicle parts and to inform maintenance necessity.

• 응용통계연구
• /
• 제30권2호
• /
• pp.233-241
• /
• 2017

구간 중도 절단 자료는 관측 연구에서 종종 발생되는 생존 자료의 한 유형으로 관심 있는 사건 발생 시간을 정확하게 관측할 수 없는 대신에 이를 포함한 두 관측 시점으로 구성된다. 본 연구의 목적은 경쟁 위험이 구간 중도 절단 자료에서 발생될 경우, 두 그룹의 누적 발생 함수를 비교하기 위한 검정 통계량을 제시하는 것이다. 특히 본 연구에서는 다중 대체 방법을 통해 생성된 자료를 이용하여 검정력과 유의 수준을 구하고자 한다. 모의실험을 통해 제안한 방법이 다양한 경우에서 적절한 결과를 보이는지 검토하였으며 실제 자료 분석의 예로 남녀 그룹의 HIV 발생 함수의 차이를 비교하기 위해 제안한 방법을 적용하였다.

• Journal of the Korean Data and Information Science Society
• /
• 제14권3호
• /
• pp.451-459
• /
• 2003

The present paper suggests a method to estimate confidence interval using SV(Support Vector) in LS-SVM(Least-Squares Support Vector Machine). To get the proposed method we used the fact that the values of the hessian matrix obtained by full data set and SV are not different significantly. Since the suggested method implement only SV, a part of full data, we can save computing time and memory space. Through simulation study we justified the proposed method.

• Journal of the Korean Data and Information Science Society
• /
• 제15권1호
• /
• pp.263-271
• /
• 2004

This article presents a new measure of chance-corrected interobserver agreement among multivariate ratings of many observers. Modifying an approach by Berry and Mielke, a new agreement measure is proposed. The important modificaton is to use the volume of simplex composed of data points as the disagreement masure. The proposed measure accounts agreement for multivariate interval observations among many observers. Hypothetical and real-life data sets are analyzed for illustrative purpose.

• 인터넷정보학회논문지
• /
• 제4권4호
• /
• pp.45-51
• /
• 2003

일반적으로 퍼지객체지향자료모형에서 속성값은 퍼지집합을 표현한다. 만일 퍼지객체지향자료모형에서 속성값을 구간값 퍼지집합으로 표현할 수 있다면, 퍼지객체지향자료모형에서 사용하는 속성값을 더 유연하게 표현하는 것이 가능하다. 퍼지객체지향자료모형의 상속구조에 나타나는 프레임내에 있는 속성값을 구하기 위해 구간값 퍼지집합을 사용하는 우선순위 논리곱연산을 이용하여 계산한다. 이 방법은 속성값의 소속정도가 기존의 퍼지집합이 아닌 구간값 퍼지집합으로 표현하는 지식정보처리분야에서 사용할 수 있다.

• Journal of the Korean Data and Information Science Society
• /
• 제11권2호
• /
• pp.173-179
• /
• 2000

Interval prediction based on the empirical distribution function for the class of time series with time varying coefficients is discussed. To this end, strong mixing property of the model is shown and results due to Fotopoulos et. al.(1994) are employed. A simulation study is presented to assess the accuracy of the proposed interval predictor.

• Journal of the Korean Data and Information Science Society
• /
• 제25권3호
• /
• pp.643-653
• /
• 2014

In this paper, we propose some estimators for the extreme value distribution based on the interval method and mid-point approximation method from the progressive Type-I interval censored sample. Because log-likelihood function is a non-linear function, we use a Taylor series expansion to derive approximate likelihood equations. We compare the proposed estimators in terms of the mean squared error by using the Monte Carlo simulation.

• Communications for Statistical Applications and Methods
• /
• 제17권3호
• /
• pp.309-318
• /
• 2010

The construction of asymptotic confidence intervals is considered for the difference of binomial proportions in two doubly sampled data subject to false-positive error. The coverage behaviors of several likelihood based confidence intervals and a Bayesian confidence interval are examined. It is shown that a hierarchical Bayesian approach gives a confidence interval with good frequentist properties. Confidence interval based on the Rao score is also shown to have good performance in terms of coverage probability. However, the Wald confidence interval covers true value less often than nominal level.

• 전기학회논문지
• /
• 제66권4호
• /
• pp.692-700
• /
• 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.

• 한국통신학회논문지
• /
• 제21권8호
• /
• pp.2119-2132
• /
• 1996

본 연구에서는 구간 벡터의 비선형 사상의 근사를 행하기 위한 4가지 신경회로망의 학습 알고리즘을 제안한다. 제안된 방법에 있어서, 신경회로망의 학습에 이용되는 입출력 데이터 쌓은 구간으로 구성되어 있다. 첫번째 방법은 전처리된 학습용 데이터 상을 통상의 역전파 알고리즘에 직접 응용하는 것이고, 두번째 방법은 두 개의 역전파 알고리즘을 이용하는 것이다. 세번째 방법은 구간 입출력 데이터를 처리할 수 있는 역전파 알고리즘으로 확장한 것이다. 마지막 방법은 구간 결합강도 및 구간 역치를 가진 신경회로망으로 확장한 것이다. 제안된 이 방법들은 컴퓨터 시뮬레이션에 의해 서로 비교 평가된다.