• 한국정보시스템학회지:정보시스템연구
• /
• 제25권2호
• /
• pp.153-171
• /
• 2016

Purpose This study suggests the development of forecasting model for local cable TV advertisement. In order to verify the expected effect of the suggestion, using the causal loop map of System Dynamics, the factors affecting the prospects of cable TV commercial market were divided into 5 groups. Then targeting 97 people involved in the cable TV commercial market in Busan, Ulsan, and Gyeongnam, a survey was conducted on their perception of the current status of local advertisement market and future prospect. Design/methodology/approach The analysis of the collected data shows that workers in advertising and advertisers perceive the influence of cable TV as an advertising media to be high, while clearly understanding the problems of cable TV commercial market. Based on this the effects on the prospects of cable TV commercial market were analyzed and a forecasting method called Weighted Moving Average was applied. In order to improve accuracy of the added value of Weighted Moving Average, the 5 factors were divided into qualitative factors and quantitative factors, and using Multi-attribute Decision Making method, all the factors were normalized and weighting factors were deduced. The result of simulating the prospects of cable TV commercial market using Weighted Moving Average, both qualitative and quantitative factors showed downward turn in the market prospect for the following 10 years. Findings The result reflects generally negative perception of advertisement viewers about the prospects of cable TV commercial market. Compared to the previous studies on domestic cable TV commercials that focused on policy suggestions and surveys on perception of current status, this study has its significance in that it used scientific method and simulation for verification.

• 말소리와 음성과학
• /
• 제2권4호
• /
• pp.145-151
• /
• 2010

In this paper, a robust feature compensation method is proposed for improving the performance of speech recognition. The proposed method is incorporated into the auto-regressive moving average (ARMA) based feature compensation. We employ variable weights for the ARMA filter according to the degree of speech activity, and pass the normalized cepstral sequence through the weighted ARMA filter. Additionally when normalizing the cepstral sequences in training, the cepstral means and variances are estimated from total training utterances. Experimental results show the proposed method significantly improves the speech recognition performance in the noisy and reverberant environments.

• Journal of the Korean Data and Information Science Society
• /
• 제26권4호
• /
• pp.907-914
• /
• 2015

저출산으로 인한 학생수의 감소는 교육 행정 정책에 있어서 매우 많은 변화들을 예고하고 있다. 본 연구는 2032년까지 정확한 학생 (인구) 수를 예측하기 위하여 연령 진급률 혹은 학년 진급률을 이용한 학생 (인구) 수를 추계하는 방법을 제시하는데 목적이 있다. 비례법을 이용한 이동평균비례법과 가중비례이동평균법이 인구추계의 방법으로 제시되었다. 제시된 방법들의 측정오차들에 대한 평균과 표준편차들을 모의실험을 통하여 구하였다. 본 연구에서 제시된 가중비례이동평균법과 이동평균비례법의 예측결과들은 낮게 추정되는 현상이 나타나고 있다. 이를 보완하여 대구 경북 지역의 고등학교 3학년 학생수를 추계하였다.

• 품질경영학회지
• /
• 제19권2호
• /
• pp.172-180
• /
• 1991

The null hypothesis being tested by $the{\bar{X}}$ control chart is that the process is in control at a quality level ${\mu}o$. An ${\bar{X}}control$ chart is a tool for detecting process average changes due to assingnable causes. The major weakness of $the{\bar{X}}$ control chart is that it is relatively insensitive to small changes in the population mean. This paper presents one way to remedy this weakness is to allow each plotted value to depend not only on the most recent subgroup average but on some of the other subgroup averages as well. Two approaches for doing this are based on (1) moving averages and (2) exponentially weighted moving averages of forecasting method.

• Industrial Engineering and Management Systems
• /
• 제4권1호
• /
• pp.75-81
• /
• 2005

Borror et al. discussed the EWMA(Exponentially Weighted Moving Average) chart to monitor the count of defects which follows the Poisson distribution, referred to the $EWMA_c$ chart, as an alternative Shewhart c chart. In the $EWMA_c$ chart, the Markov chain approach is used to calculate the ARL (Average Run Length). On the other hand, in order to monitor the process fraction defectives P in high-yield processes, Xie et al. presented the CCC(Cumulative Count of Conforming)-r chart of which quality characteristic is the cumulative count of conforming item inspected until observing $r({\geq}2)$ nonconforming items. Furthermore, Ohta and Kusukawa presented the $CS(Confirmation Sample)_{CCC-r}$ chart as an alternative of the CCC-r chart. As a more superior chart in high-yield processes, in this paper we present an $EWMA_{CCC-r}$ chart to detect more sensitively small or moderate shifts in P than the $CS_{CCC-r}$ chart. The proposed $EWMA_{CCC-r}$ chart can be constructed by applying the designing method of the $EWMA_C$ chart to the CCC-r chart. ANOS(Average Number of Observations to Signal) of the proposed chart is compared with that of the $CS_{CCC-r}$ chart through computer simulation. It is demonstrated from numerical examples that the performance of proposed chart is more superior to the $CS_{CCC-r}$ chart.

• 한국가스학회지
• /
• 제18권1호
• /
• pp.8-16
• /
• 2014

본 연구에서는 국내에서 발생한 가스사고를 분석하여 가스사고의 건수예측모델에 대하여 제시하였다. 가스사고 건수를 예측하기 위하여 단순이동평균법(3,4,5기간), 가중이동평균법 및 지수평활법을 적용해 본 결과, 4기간 이동평균법과 가중이동평균법에 의한 모델의 평균오차제곱합이 44.4와 43으로 가장 정확성이 높은 것으로 나타났다. 가스사고 발생건수 예측시스템을 개발함으로서 가스사고 예방활동에 적극 활용할 수 있을 것이다.

• Journal of the Korean Data and Information Science Society
• /
• 제22권6호
• /
• pp.1065-1074
• /
• 2011

1990년대 중반 이후 금융 분야에서 가장 많은 관심을 받는 연구 주제 중의 하나는 대표적인 위험측정 방법인 VaR (Value at risk)이다. VaR는 주어진 신뢰수준에서 정상적인 시장조건을 가정할 때 선택한 목표기간 동안 발생할 수 있는 포트폴리오의 최대손실액으로 정의된다. 본 논문에서는 국내 주가지수 자료를 이용한 포트폴리오에 다변량 정규분포를 이용하는 VaR 예측 방법인 단순이동평균법과 지수가중이동평균법을 고려하여 VaR를 예측한 결과와 t 분포 및 조건부 코퓰라 (Copula) 함수를 이용하여 VaR를 예측한 결과를 비교 평가하였다. 자료 분석 결과에 의하면 포트폴리오 구성 종목 간에 종속성구조와 비정규성이 존재하는 경우에 t 분포와 조건부 코퓰라 방식을 이용하여 VaR 추정의 정확도를 높일 수 있다는 결론을 얻을 수 있었다.

• 디지털융복합연구
• /
• 제11권8호
• /
• pp.183-190
• /
• 2013

PPG 신호는 심장의 박동에 동기된 유사 주기 신호이다. 본 논문에서는 PPG 신호의 유사주기성을 이용한 지수가중 이동평균필터 방법을 제안한다. 이 필터링 방법은 PPG 신호를 주기적으로 분리하여 각 주기 신호의 같은 순번에 있는 샘플들끼리 평균을 취하는 방법이다. 연속된 PPG 신호의 주기중에 동잡음이 혼입되었다면 주기를 기준으로 PPG 신호를 분리한 후, 각 주기의 샘플수를 조정하여 같은 샘플수를 가지게 만든다. 이 주기들을 2차원으로 배열한 후 현재 주기부터 이전 각 주기의 샘플끼리 평균을 취함으로써 훼손없이 동잡음을 제거할 수 있었다.

• 대한전기학회논문지
• /
• 제35권5호
• /
• pp.193-198
• /
• 1986

In this paper, 1-168 hours ahead load prediction algorithm is developed for power system economic weekly operation. Total load is composed of three components, which are base load, week load and weather-sensitive load. Base load and week load are predicted by moving average and exponential smoothing method, respectively. The days of moving average and smoothing constant are optimally determined. Weather-sensitive load is modeled by linear form. The paramiters of weather load model are estimated by exponentially weighted recursive least square method. The load prediction of special day is very tedious, difficult and remains many problems which should be improved. Test results are given for the day of different types using the actual load data of KEPCO.

• 통합자연과학논문집
• /
• 제7권3호
• /
• pp.200-207
• /
• 2014

Average number of samples to signal (ANSS) and average time to signal (ATS) are the most widely used criterion for comparing the efficiencies of the quality control charts. In this study the method of evaluating ANSS and ATS values of the multivariate exponentially weighted moving average (EWMA) control charts with Markov chain approach was presented when the production process is in control state or out of control state. Through numerical results, it is found that when the number of transient state r is less than 50, the calculated ANSS and ATS values are unstable; and ATS(r) tends to be stabilized when r is greater than 100; in addition, when the properties of multivariate EWMA control chart is evaluated using Markov chain method, the number of transient state r requires bigger values when the smoothing constatnt ${\lambda}$ becomes smaller.