• Title/Summary/Keyword: 단순이동평균

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ESD(Exponential Standard Deviation) Band centered at Exponential Moving Average (지수이동평균을 중심으로 하는 ESD밴드)

  • Lee, Jungyoun;Hwang, Sunmyung
    • Journal of Intelligence and Information Systems
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    • v.22 no.2
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    • pp.115-125
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    • 2016
  • The Bollinger Band indicating the current price position in the recent price action range is obtained by adding/substracting the simple standard deviation (SSD) to/from the simple moving average (SMA). In this paper, we first compare the characteristics of the SMA and the exponential moving average (EMA) in the operator's point of view. A basic equation is obtained between the interval length N of the SMA operator and the weighting factor ${\rho}$ of the EMA operator, that makes the centers of the 1st order momentums of each operator impulse respoinse identical. For equivalent N and ${\rho}$, frequency response examples are obtained and compared by using the discrete time Fourier transform. Based on observation that the SMA operator reacts more excessively than the EMA operator, we propose a novel exponential standard deviation (ESD) band centered at the EMA and derive an auto recursive formula for the proposed ESD band. Practical examples for the ESD band show that it has a smoother bound on the price action range than the Bollinger Band. Comparisons are also made for the gap corrected chart to show the advantageous feature of the ESD band even in the case of gap occurrence. Trading techniques developed for the Bollinger Band can be straight forwardly applied to those for the ESD band.

A study on estimating piecewise linear trend model using the simple moving average of differenced time series (차분한 시계열의 단순이동평균을 이용하여 조각별 선형 추세 모형을 추정하는 방법에 대한 연구)

  • Okyoung Na
    • The Korean Journal of Applied Statistics
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    • v.36 no.6
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    • pp.573-589
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    • 2023
  • In a piecewise linear trend model, the change points coincide with the mean change points of the first differenced time series. Therefore, by detecting the mean change points of the first differenced time series, one can estimate the change points of the piecewise linear trend model. In this paper, based on this fact, a method is proposed for detecting change points of the piecewise linear trend model using the simple moving average of the first differenced time series rather than estimates of the slope or residuals. Our Monte Carlo simulation experiments show that the proposed method performs well in estimating the number of change points not only when the error terms in the piecewise linear trend model are independent but also when they are serially correlated.

Comparison of Pedestrian Walking Characteristics Between Highway Crosswalk and Pedestrian Underpass (횡단보도와 지하보도간의 횡단보행특성 비교)

  • 임종훈;김동녕
    • Journal of Korean Society of Transportation
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    • v.18 no.5
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    • pp.17-29
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    • 2000
  • 본 연구는 지하횡단보도 이용시 계단에서 나타나는 보행자 특성에 관한 연구로써, 교차로에서 횡단보도와 지하보도에서 보행자의 편의성을 정량화한 것이다. 지하보도 계단에서의 보행자특성에 관한 연구, 즉 속도, 밀도와 보행자교통량에 관한 연구는 비디오촬영을 통하여 수집한 자료를 분석하였다. 지하보도나 횡단보도 횡단시 이동 거리, 소요시간, 소요에너지는 보행자특성 분석에서 나온 결과와 직접 시설을 조사한 자료를 이용하여 비교하였다. 주요 연구결과는 다음과 같다. 첫째, 지하보도 계단에서 보행자 속도는 상향이동시의 평균속도는 37.7m/분(또는 0.67m/초)이고, 하향이동시의 평균속도는 46.7m/분(또는 0.77m/초)으로 나타났다. 둘째, 평균 이동거리는 단순횡단의 경우 지하보도는 119m이고, 횡단보도는 78m이다. 대각횡단의 경우 지하 보도는 161m이고, 횡단보도는 111m이다. 평균 소요시간은 단순횡단의 경우 지하보도는 125.6초이고, 횡단보도는 111.3초로 나타났다. 대각횡단의 경우 지하보도는 162.3초이고, 횡단보도는 178.8초로 나타났다. 평균 소요에너지는 단순횡단의 경우 지하보도는 20.2kcal이고, 횡단보도는 4.7kcal이다. 대각횡단의 경우 지하보도는 23.5kcal이고, 횡단보도는 6.6kcal이다. 단순횡단시 지하보도가 횡단보도보다 이동거리는 평균 1.5배 더 길고, 시간은 평균 1.2배 더 소요되고, 에너지는 평균 4.5배가 더 소요된다. 대각횡단시 이동거리는 평균 1.5배 더 길고, 소요시간은 비슷하고, 에너지는 평균 3.5배 더 소요되었다. 본 연구는 기존의 교차로나 가로구간에 지하보도만 설치되어 있는 지점에 횡단보도의 설치여부에 관한 정책결정을 하는데 도움이 될 수 있을 것이다.

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Real-time Confidence interval estimation for Improved accuracy of Ship-inside the anomaly detection (선박내부 이상감지의 정확도 향상을 위한 실시간 신뢰구간 추정)

  • Kim, Yeong-Ju;Heo, yu Kyung;Jeong, Majung-A
    • Proceedings of the Korea Information Processing Society Conference
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    • 2014.04a
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    • pp.721-723
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    • 2014
  • 본 논문은 선박내부의 센서데이터 이상감지를 위해 실시간 신뢰구간을 설정하고 신뢰구간을 초과하거나 미만이 되면 경보를 통해 관리자에게 알려주는 모니터링을 위한 신뢰구간 추정이다. 여기서, 이상 감지 예측의 정확도 향상을 위해 단순지수평활법과 이동평균법의 평균제곱오차를 비교 평가 하였다. 실험결과, 이동평균법의 평균제곱오차가 단순지수평활법 보다 적게 나와 선박 내부 모니터링을 위한 신뢰구간은 이동평균법을 적용하였다.

Forecasting the Time-Series Data Converged on Time PLOT and Moving Average (Time PLOT과 이동평균 융합 시계열 데이터 예측)

  • Lee, Jun-Yeon
    • Journal of the Korea Convergence Society
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    • v.6 no.4
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    • pp.161-167
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    • 2015
  • It is very difficult to predict time-series data. This is because data obtained from the signal having a non-linear characteristic has an uncertainty. In this paper, By differentiating time-series data is the average of the past data under the premise that change depending on what pattern, and find the soft look of time-series change pattern. This paper also apply the probability variables to generalize time-series data having a specific data according to the reflection ratio of the differentiation. The predicted value is estimated by removing cyclic movement and seasonal fluctuation, and reflect the trend by extracting the irregular fluctuation. Predicted value has demonstrated the superiority of the proposed algorithm and compared with the best results by a simple moving average and the moving average.

A Study on the Travel Speed Estimation Using Bus Information (버스정보기반 통행속도 추정에 관한 연구)

  • Bin, Mi-Young;Moon, Ju-Back;Lim, Seung-Kook
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.12 no.4
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    • pp.1-10
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    • 2013
  • This study was conducted to investigate that bus information was used as an information of travel speed. To determine the travel speed on the road, bus information and the information collected from the point detector and the interval detection installed were compared. If bus information has the function of traffic information detector, can provide the travel speed information to road users. To this end, the model of recognizing the traffic patterns is necessary. This study used simple moving-average method, simple exponential smoothing method, Double moving average method, Double exponential smoothing method, ARIMA(Autoregressive integrated moving average model) as the existing methods rather than new approach methods. This study suggested the possibility to replace bus information system into other information collection system.

폐쇄적플랫폼에서 오픈환경으로진화

  • Han, In-Gyu
    • Digital Contents
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    • no.11 s.150
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    • pp.68-71
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    • 2005
  • 이동전화가단순히음성을송수신하는데에서데이터를전송하는방향으로진화하면서 인터넷과이동통신이결합되는현상이나타나게됐다. 초기에는데이터전송속도가 14.4Kbps(IS-95A)에불과했지만퀄컴의MSM3000 칩이출시된이후1999년에는 평균64Kbps, 최대전송속도115Kbps의IS-95B로발전하게됐다.

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A numerical study on portfolio VaR forecasting based on conditional copula (조건부 코퓰라를 이용한 포트폴리오 위험 예측에 대한 실증 분석)

  • Kim, Eun-Young;Lee, Tae-Wook
    • Journal of the Korean Data and Information Science Society
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    • v.22 no.6
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    • pp.1065-1074
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    • 2011
  • During several decades, many researchers in the field of finance have studied Value at Risk (VaR) to measure the market risk. VaR indicates the worst loss over a target horizon such that there is a low, pre-specified probability that the actual loss will be larger (Jorion, 2006, p.106). In this paper, we compare conditional copula method with two conventional VaR forecasting methods based on simple moving average and exponentially weighted moving average for measuring the risk of the portfolio, consisting of two domestic stock indices. Through real data analysis, we conclude that the conditional copula method can improve the accuracy of portfolio VaR forecasting in the presence of high kurtosis and strong correlation in the data.

Anomaly Detection and Performance Analysis using Deep Learning (딥러닝을 활용한 설비 이상 탐지 및 성능 분석)

  • Hwang, Ju-hyo;Jin, Kyo-hong
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2021.10a
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    • pp.78-81
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    • 2021
  • Through the smart factory construction project, sensors can be installed in manufacturing production facilities and various process data can be collected in real time. Through this, research on real-time facility anomaly detection is being actively conducted to reduce production interruption due to facility abnormality in the manufacturing process. In this paper, to detect abnormalities in production facilities, the manufacturing data was applied to deep learning models Autoencoder(AE), VAE(Variational Autoencoder), and AAE(Adversarial Autoencoder) to derive the results. Manufacturing data was used as input data through a simple moving average technique and preprocessing process, and performance analysis was conducted according to the window size of the simple movement average technique and the feature vector size of the AE model.

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A Scheme to Support IP Mobility over Wireless ATM Networks (무선 ATM망에서 이동성 지원 기법)

  • 문영성;김영욱
    • Journal of KIISE:Information Networking
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    • v.30 no.5
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    • pp.573-580
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    • 2003
  • Increasing user demand for the more bandwidths in wireless communications has motivated a new challenge to utilize the benefits of wireless ATM technology This paper focuses on how to provide IP services to a mobile user over wireless ATM networks. By enhancing the NHRP standard, several shortcomings are improved that are resulted from the naive combinations of Mobile IP over ATM and IP over wireless ATM. This paper presents a mobile location management algorithm that is referred to as the Mobile NHRP scheme. The mobile tracking procedure and the mobile locating procedure are explicitly defined in the proposed scheme. On the locating procedure, the source station may obtain the current location of the destination from NHSs(Next Hop Servers). Therefore the optimized connection can be setup directly. The total costs per move and per setup over ATM/IP overlaid networks are estimated.