• 한국수자원학회논문집
• /
• 제39권12호
• /
• pp.997-1012
• /
• 2006

본 연구에서는 조건부 핵밀도함수와 CAFPE(Corrected Asymptotic Final Prediction Error) 차수결정 방법에 근거한 비매개변수적 비선형 자기회귀 (Nonlinear AutoRegressive, NAR) 모형을 소개하고 이를 SOI(Southern Oscillation Index)에 적용하였다. SOI 자료에 대해서 선형 AR 모형을 적용하였으나 잔차에 대한 검정결과 이분산성(heteroscedasticity)을 나타내었다. 또한 BDS(Brock-Dechert-Sheinkman) 검정에서 비선형성이 존재함을 확인하였다. 따라서 NAR 모형에 SOI 자료를 적용시켰다. CAFPE를 이용하여 가장 적합한 모형으로 지체 1, 2와 4가 선택되었으며 조건부 평균함수를 추정하여 SOI 자료를 모의한 결과 잔차에 대해서 정규성과 이분산성 가정이 Jarque-Bera 검정과 ARCH-LM 검정에서 각각 기각되었으며 또한 조건부 표준편차함수의 최적 차수로 3, 8과 9가 CAPFE를 통해 선택되었다. 조건부 평균함수와 표준편차함수를 모두 고려한 모형에 대한 잔차 검정 결과 잔차의 I.I.D 가정을 만족하였으며 특히, BDS 검정에서 신뢰구간 95%와 99%에서 모두 만족한 결과를 나타내었다. 마지막으로 전체의 15%에 해당하는 SOI 자료에 대해서 One-Step 예측을 수행하였으며 선형 모형에 비해 평균제곱예측오차가 7% 적게 나타났다. 따라서, NAR 모형은 여타의 매개변수적 방법과 달리 모형 선택에 있어 자유로우며 비선형성을 고려할 수 있는 모형으로서 SOI 자료와 같은 비선형 자료를 위한 모의방법으로 선형 모형에 비해 많은 장점을 가지고 있다.

• 응용통계연구
• /
• 제32권4호
• /
• pp.631-642
• /
• 2019

다수의 항목무응답이 발생한 표본조사에서는 추정의 정확성이 떨어진다. 이를 해결하기 위한 많은 방법이 개발되었으나 응답률이 관심변수에 의해 영향을 받는 경우임에도 이를 고려하지 않고 랜덤으로 무응답이 발생한다는 가정 하에서 사용하는 무응답 처리 방법을 사용하게 되면 편향이 발생하는 것으로 알려져 있다. Chung과 Shin (2017)과 Min과 Shin (2018)은 응답률이 관심변수의 함수인 경우에서 발생된 편향을 적절히 처리하여 추정의 정확성을 향상시키는 방법을 제안하였다. 본 연구에서는 응답률 함수가 선형(linear)이면서 초모집단 모형의 오차가 정규분포를 따르는 경우를 살펴보았으며 층별 모집단 수가 편향 보정에 영향을 주는지도 살펴보았다. 모의실험을 통하여 제안된 추정량의 성능을 살펴보았으며 실제 자료 분석을 통해 이를 확인하였다.

• International Journal of Control, Automation, and Systems
• /
• 제6권5호
• /
• pp.639-650
• /
• 2008

Electricity price forecasting has become an integral part of power system operation and control. In this paper, a wavelet transform (WT) based neural network (NN) model to forecast price profile in a deregulated electricity market has been presented. The historical price data has been decomposed into wavelet domain constitutive sub series using WT and then combined with the other time domain variables to form the set of input variables for the proposed forecasting model. The behavior of the wavelet domain constitutive series has been studied based on statistical analysis. It has been observed that forecasting accuracy can be improved by the use of WT in a forecasting model. Multi-scale analysis from one to seven levels of decomposition has been performed and the empirical evidence suggests that accuracy improvement is highest at third level of decomposition. Forecasting performance of the proposed model has been compared with (i) a heuristic technique, (ii) a simulation model used by Ontario's Independent Electricity System Operator (IESO), (iii) a Multiple Linear Regression (MLR) model, (iv) NN model, (v) Auto Regressive Integrated Moving Average (ARIMA) model, (vi) Dynamic Regression (DR) model, and (vii) Transfer Function (TF) model. Forecasting results show that the performance of the proposed WT based NN model is satisfactory and it can be used by the participants to respond properly as it predicts price before closing of window for submission of initial bids.

• Journal of applied mathematics & informatics
• /
• 제5권2호
• /
• pp.373-382
• /
• 1998

Most of the works in Time Series Analysis are based on the Auto Regressive Integrated Moving Average (ARIMA) models presented by Box and Jeckins(1976). If the data exhibits no ap-parent deviation from stationarity and if it has rapidly decreasing autocorrelation function then a suitable ARIMA(p,q) model is fit to the given data. Selection of the orders of p and q is one of the crucial steps in Time Series Analysis. Most of the methods to determine p and q are based on the autocorrelation function and partial autocor-relation function as suggested by Box and Jenkins (1976). many new techniques have emerged in the literature and it is found that most of them are over very little use in determining the orders of p and q when both of them are non-zero. The Durbin-Levinson algorithm and Innovation algorithm (Brockwell and Davis 1987) are used as recur-sive methods for computing best linear predictors in an ARMA(p,q)model. These algorithms are modified to yield an effective method for ARMA model identification so that the values of order p and q can be determined from them. The new method is developed and its validity and usefulness is illustrated by many theoretical examples. This method can also be applied to an real world data.

• 한국농공학회논문집
• /
• 제55권6호
• /
• pp.37-46
• /
• 2013

Many factors about the stability for the reservoir embankments is determined when the facility is completed. Therefore the initial design of the embankment is important. Many researchers focused the effect of soil parameters although the cross section greatly affects the stability and can be controlled in design step. The objective of this research is to analysis of the effects for the safety factor of slope and seepage according to change cross-section in embankment. As a result, the quantity of seepage decreased as the gradient of downstream slope decreased and was proportional to the height of embankments. There was a linear relationship between the gradient of slope and the safety factor of slope. However the gradient of slope did not affect other side slope. All in a relationship, regressive equations with a high correlation coefficient were calculated and can be applied the simple estimation method of the stability using the cross-section. As results of analyzing the sensitivity, the friction angle and permeability critically effect for the slope stability and the seepage, respectively. The effect of the slope gradient was similar to major soil properties.

• 한국수학교육학회지시리즈A:수학교육
• /
• 제50권1호
• /
• pp.103-118
• /
• 2011

The study examined whether the relation between mathematics self-efficacy and mathematics achievement was partially mediated by the learning strategies, using latent growth model analyses. It was also examined the auto-regressive, cross-lagged (ARCL) panel model for testing the stability and change in the relation of mathematics self-efficacy and learning strategy over time. The study analyzed the first-year to the third-year data of the Korean Educational Longitudinal Survey (KELS). The result of ARCL panel model analysis showed that earlier mathematics self-efficacy could predict later learning strategy use. There were linear trends in mathematics self-efficacy, learning strategy, and mathematics achievement. Specifically, mathematics achievement was increased over the three time points, whereas mathematics self-efficacy and learning strategies were significantly decreased. In the analyses of latent growth models, the mediating effects of learning strategies were overall supported. That is, both of initial status and change rate of rehearsal strategy partially mediated the relation of mathematics self-efficacy and mathematics achievement. However, in elaboration and meta-cognitive strategies, only the initial status of each variable showed the indirect relationship.

• 대한두개안면성형외과학회지
• /
• 제10권1호
• /
• pp.7-13
• /
• 2009

Purpose: Endoscopic transnasal correction of the medial orbital fractures cannot be enable to confirm the reduction degree of orbital volume without imaging modalities. We have intended through this study to make a quantative analysis of preoperative orbital volume increment and the reduction degree of that after ethmoidal sinus packing by using CT scan. Methods: In this retrospective study, 22 patients were selected to evaluate the postoperative volume reduction, who took 2 CT scans which are pre- and postoperative under the same protocol. The postoperative CT scan was carried out in about 5 days after the operation with the packing inserted into ethmoidal sinus. The length of bony defect on each section was measured by PACS program and the area of defect was calculated by summing lengths on each section multiplied by the thickness of the section. When the outline of orbit on the slice is drawn manually with a cursor, PACS program measures the area automatically. Orbital volume was calculated from the sum of the area multiplied by the section thickness. Results: The mean dimension of fractured walls was $2.86{\pm}0.99cm^2$. The mean orbital volume of the unaffected orbits was $22.89{\pm}2.15cm^3$ and that of the affected orbits was $25.62{\pm}2.82cm^3$. The mean orbital volume increment of the affected orbits was $2.73{\pm}1.13cm^3$. After surgery, the mean orbital volume of the unaffected orbits was $22.46{\pm}2.73cm^3$ and the mean orbital volume decrease on the surgical side was $2.98{\pm}1.07cm^3$. The estimated correction rate was 118.30%. Conclusion: The orbital volume increment in fractured orbit showed linear correlation with the dimension of fractured area. The orbital volume changes after ethmoidal sinus packing also showed linear correlation with orbital volume increment in fractured orbit. This study showed the regressive linear correlation between the increment of orbital volume and the correction rate. To evaluate the maintenance of reduction state, we think that the further study should be done for comparative analysis of orbital volume change after removal of packing.

• 대한토목학회논문집
• /
• 제29권2B호
• /
• pp.163-171
• /
• 2009

수문시계열 분석과 예측을 위하여 통상적으로 기존의 선형적인 모형들을 이용하여 왔다. 그러나 최근 자연현상이나 수문시계열의 패턴 그리고 변동성에 비선형구조가 존재하고 있다는 것이 입증되고 있다. 따라서 기존의 선형적인 방법들에 의한 시계열분석이나 예측은 비선형 시스템에 대해서 적절하지 않을 것이다. 최근, 시계열의 비선형성 구조를 판단하기 위해 카오스 이론을 토대로 한 상관적분으로부터 BDS(Brock-Dechert-Scheinkman) 통계 기법이 유도되었다. BDS 통계는 시스템의 비선형구조와 무작위성 구조를 구별하는데 매우 효과적으로 이용되어 오고 있다. 또한 DVS(Deterministic Versus Stochastic) 알고리즘은 카오스와 추계학적 시스템을 구별하고 예측하는데 주로 이용되어 왔다. 그러나 본 연구에서는 DVS 알고리즘에 의해 시계열의 비선형성을 판별할 수 있음을 보이고자 한다. 따라서 본 연구에서는 추계학적 시계열과 수문학적 시계열들의 비선형성을 검사하고자 한다. ARMA 모형과 TAR(Threshold autoregressive) 모형으로부터로 발생시킨 추계학적 시계열, 미국 유타주 GSL 체적자료, 미국 플로리다 주 St. Johns 강 Cocoa 지점의 유출량 자료, 소양강 댐 일 유입량 자료 등의 수문시계열에 대해 비선형성 분석을 수행하고 그 결과를 비교하였다. 분석결과 BDS 통계가 선형 및 비선형 시계열을 구분하는데 매우 강력한 도구임을 보였고, DVS 알고리즘 또한 시계열의 비선형성을 구별하는데 효과적으로 이용될 수 있음을 보였다.

• 한국정보통신학회논문지
• /
• 제22권2호
• /
• pp.284-294
• /
• 2018

모바일 스마트 장치 배터리의 남은 시간 예측에 통계적 기법이 많이 사용되고 있다. 그러나 특정 통계 기법만을 사용한 기존 연구들의 결과만으로는, 통계적 기법이 배터리의 남은 시간 예측에 적합한지가 판단하기 어렵다. 이에 본 논문에서는 스마트 장치 배터리의 남은 시간 예측에 적용 가능한 다양한 통계 기법들의 성능을 평가하였다. 평가에 사용된 통계 예측 기법은 단순 및 이동 평균, 선형 회귀, 다변수 적응 회귀, 자기 회귀, 다항식 회귀, 이중 및 삼중 지수평활 기법이다. 분석 결과는, 향후 통계적 기법을 배터리 남은 사용 시간 예측에 적용하려는 IT 엔지니어에게 중요한 자료로 활용될 수 있다.

• Imaging Science in Dentistry
• /
• 제44권1호
• /
• pp.21-29
• /
• 2014

Purpose: To determine the conversion coefficients (CCs) from the dose-area product (DAP) value to effective dose in cone-beam CT. Materials and Methods: A CBCT scanner with four fields of view (FOV) was used. Using two exposure settings of the adult standard and low dose exposure, DAP values were measured with a DAP meter in C mode ($200mm{\times}179mm$), P mode ($154mm{\times}154mm$), I mode ($102mm{\times}102mm$), and D mode ($51mm{\times}51mm$). The effective doses were also investigated at each mode using an adult male head and neck phantom and thermoluminescent chips. Linear regressive analysis of the DAP and effective dose values was used to calculate the CCs for each CBCT examination. Results: For the C mode, the P mode at the maxilla, and the P mode at the mandible, the CCs were 0.049 ${\mu}Sv/mGycm^2$, 0.067 ${\mu}Sv/mGycm^2$, and 0.064 ${\mu}Sv/mGycm^2$, respectively. For the I mode, the CCs at the maxilla and mandible were 0.076 ${\mu}Sv/mGycm^2$ and 0.095 ${\mu}Sv/mGycm^2$, respectively. For the D mode at the maxillary incisors, molars, and mandibular molars, the CCs were 0.038 ${\mu}Sv/mGycm^2$, 0.041 ${\mu}Sv/mGycm^2$, and 0.146 ${\mu}Sv/mGycm^2$, respectively. Conclusion: The CCs in one CBCT device with fixed 80 kV ranged from 0.038 ${\mu}Sv/mGycm^2$ to 0.146 ${\mu}Sv/mGycm^2$ according to the imaging modes and irradiated region and were highest for the D mode at the mandibular molar.