• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2002년도 추계학술발표논문집 (하)
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• pp.2447-2450
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• 2002

주가지수선물시장은 주식투자에 따르는 위험을 효과적으로 관리할 수 있는 제도적 장치로서 오늘날 불안한 주식시장 현황에 있어서 더욱더 중요한 위치를 갖고 있다. 현재 이러한 주가지수선물거래에 있어서 Moving Average 를 예측하고자 하는 여러 트레이딩 시스템을 선보이고 있다. 이 논문에서는 과거의 데이터를 토대로 한 Moving Average Line 분석에 있어서 일반적으로 기존방법보다 효과적이라고 알려진 유전자 알고리즘을 이용하여 Moving Average 의 최적 Period 예측 시스템을 구현한다.

• 지질공학
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• 제17권4호
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• pp.507-510
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• 2007

지하수위와 강우이동평균의 상관관계를 낙동강 유역의 여러 관측소 자료를 근거로 하여 분석하였다. 강우자료와 강우관측소의 하류 방향으로 인접한 지하수위 관측소의 지하수위자료를 비교분석하였고 강우자료를 여러 범위의 기간 동안 이동평균하여 지하수위자료와의 상관관계를 분석하였고 최대상관계수를 가지는 이동평균기간을 구하였다. 낙동강 유역의 강우와 지하수위의 분석에서 대체로 12월에서 4월까지 갈수기에서 지하수위의 현저한 저하를 확인할 수 있었고 지하수 위와 강우이동평균의 상관관계를 분석한 결과 20일에서 80일 범위의 이동평균값에서 가장 높은 상관계수를 구할 수 있었다.

• 지질공학
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• 제18권4호
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• pp.393-403
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• 2008

한국의 남부지방인 경상남도와 전라남도에서 강수량과 지하수위의 관계를 분석해보고 강수량 이동평균과 지하수위의 상관관계를 분석하였다. 한국 남부지방의 여러 관측소에서 지하수위를 분석한 결과 지역적으로 다소 다른 지하수위의 계절적인 변동을 보여주었다. 지하수위는 강수량이 적은 봄철에 떨어지고 여름철 풍수기에 상승하는 경향을 보이나 그 변동 폭은 지역별로 다른 양상을 보인다. 지하수위와 강우이동평균의 상관관계를 여러 관측소의 자료로 분석한 결과 20일에서 130일 범위의 이동평균값에서 가장 높은 상관관계를 보여주었다. 그리고 유역평균 일최대침투량인 한계침투량은 한국 남부지방에서는 10 mm에서 90 mm 범위의 값을 가지는 것으로 분석되었다. 한계침투량을 고려해서 수정된 강수자료를 이용하여 이동평균을 구하여 지하수위와의 상관관계를 구해본 결과 이동평균일의 범위는 10일에서 150일 이었고, 한계침투량을 고려했을 때 더 큰 상관계수를 가지는 것으로 나타났다.

• 한국환경과학회지
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• 제30권7호
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• pp.519-527
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• 2021

Moving average precipitation provides periodic precipitation patterns by solving precipitation irregularities. However, due to uncertain moving average periods, excessive data smoothing occurs, which limit the possibility to analyze groundwater levels in the short term. Nonetheless, groundwater level fluctuation can compensate these limitations as it can calculate appropriately for unit time and verify the effect of precipitation penetrated into groundwater in a short time period. In this study, the characteristics of groundwater level were evaluated using groundwater level fluctuation to compensate for limitations of groundwater level analysis using moving average precipitation. In addition, the groundwater quality was investigated using the electrical conductivity fluctuation. The study site was Hyogyo-ri, Yesan-si, Chungcheongnam-do. Four observation wells and an automated weather system were used. The correlation between groundwater level fluctuation and precipitation (Case 1) and the correlation between groundwater level and moving average precipitation (Case 3) were compared. In the analysis for 1 hour data, the correlation coefficient of Case 1 was higher than that of Case 3, and in the analysis for 1 day data, the correlation coefficient of Case 3 was higher than that of Case 1.

• 한국의류산업학회지
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• 제19권3호
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• pp.289-295
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• 2017

This study aims to develop clothing sales forecast system using weather information. As the annual temperature variation affects changes in daily sales of seasonal clothes, sales period can be predicted growth, peak and decline period by changes of temperature. From this perspective, we analyzed the correlation between temperature and sales. Moving average method was applied in order to indicate long-term trend of temperature and sales changes. 7-day moving average temperature at the start/end points of the growth, peak, and decline period of S/S clothing sales was calculated as a reference temperature for sales forecast. According to the 2013 data analysis results, when 7-day moving average temperature value becomes $4^{\circ}C$ or higher, the growth period of S/S clothing sales starts. The peak period of S/S clothing sales starts at $17^{\circ}C$, up to the highest temperature. When temperature drops below $21^{\circ}C$ after the peak temperature, the decline period of S/S clothing sales is over. The reference temperature was applied to 2014 temperature data to forecast sales period. Through comparing the forecasted sales periods with the actual sales data, validity of the sales forecast system has been verified. Finally this study proposes 'clothing sales forecast system using weather information' as the method of clothing sales forecast.

• International Journal of Control, Automation, and Systems
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• 제5권6호
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• pp.701-706
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• 2007

The measurement accuracy for heart rate or $SpO_2$ using photoplethysmography (PPG) is influenced by how well the noise from motion artifacts and other sources can be removed. Eliminating the motion artifacts is particularly difficult since its frequency band overlaps that of the basic PPG signal. Therefore, we propose the Periodic Moving Average Filter (PMAF) to remove motion artifacts. The PMAF is based on the quasi-periodicity of the PPG signals. After segmenting the PPG signal on periodic boundaries, we average the $m^{th}$ samples of each period. As a result, we remove the motion artifacts well without the deterioration of the characteristic point.

• Journal of Sport and Applied Science
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• 제4권1호
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• pp.17-30
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• 2020

Moving sport tourism refers to travel that combines sport activity and tours to a particular destination. Although moving sport tourism is one of the fastest growing segments of the sport tourism industry, it is still lack of related-knowledge and academic studies. Hence, this study is conducted to explore the characteristics of moving sport tourism and to provide implications for sport tourism industry and future research. For this, ten participants who regularly participated in bicycle tours for the last 10 years were recruited for this study. The sample consisted of 9 males and 1 female. The average age of the participants was 44.6 years of which all but 2 had a full-time job. The average period of participating in bicycle tour was 7.9 years. For analysing data, content analysis approach was used. Interviews were tape recoded and data were multiple reviewed to identify the similar themes and to categorize them into conceptual constructs. Results suggest two requirements of moving sport tourism(moving and concurrent), three characteristics of moving sport tourism(self-directed, exploring, non-linear, purposive-riding, partial competitive, cultural touring) and two categories of moving sport tourism(full moving sport tourism and partial moving sport tourism). Implications for sport tourism industry and future studies were discussed.

• 대한산업공학회지
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• 제33권4호
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• pp.457-468
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• 2007

This paper proposes an adaptive moving average (A-MA) control chart with variable sampling intervals (VSI) for detecting shifts in the process mean. The basic idea of the VSI A-MA chart is to adjust sampling intervals as well as to accumulate previous samples selectively in order to increase the sensitivity. The VSI A-MA chart employs a threshold limit to determine whether or not to increase sampling rate as well as to accumulate previous samples. If a standardized control statistic falls outside the threshold limit, the next sample is taken with higher sampling rate and is accumulated to calculate the next control statistic. If the control statistic falls within the threshold limit, the next sample is taken with lower sampling rate and only the sample is used to get the control statistic. The VSI A-MA chart produces an 'out-of-control' signal either when any control statistic falls outside the control limit or when L-consecutive control statistics fall outside the threshold limit. The control length L is introduced to prevent small mean shifts from being undetected for a long period. A Markov chain model is employed to investigate the VSI A-MA sampling process. Formulae related to the steady state average time-to signal (ATS) for an in-control state and out-of-control state are derived in closed forms. A statistical design procedure for the VSI A-MA chart is proposed. Comparative studies show that the proposed VSI A-MA chart is uniformly superior to the adaptive Cumulative sum (CUSUM) chart and to the Exponentially Weighted Moving Average (EWMA) chart, and is comparable to the variable sampling size (VSS) VSI EWMA chart with respect to the ATS performance.

• 한국지구과학회지
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• 제43권4호
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• pp.539-556
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• 2022

In the coastal areas of Jeju Island, composed of volcanic rocks, saltwater intrusion occurs due to excessive pumping and geological characteristics. Groundwater level and electrical conductivity (EC) in multi-depth monitoring wells in coastal areas were characterized from 2005 to 2019. During the period of the lowest monthly precipitation, from November 2017 until February 2018, groundwater level decreased by 0.32-0.91 m. During the period of the highest monthly precipitation, from September 2019 until October 2019, groundwater level increased by 0.46-2.95 m. Groundwater level fluctuation between the dry and wet seasons ranged from 0.79 to 3.73 m (average 1.82 m) in the eastern area, from 0.47 to 6.57 m (average 2.55 m) in the western area, from 0.77 to 8.59 m (average 3.53 m) in the southern area, and from 1.06 to 12.36 m (average 5.92 m) in the northern area. In 2013, when the area experienced decreased annual precipitation, at some monitoring wells in the western area, the groundwater level decreased due to excessive groundwater pumping and saltwater intrusion. Based on EC values of 10,000 ㎲/cm or more, saltwater intrusion from the coastline was 10.2 km in the eastern area, 4.1 km in the western area, 5.8 km in the southern area, and 5.7 km in the northern area. Autocorrelation analysis of groundwater level revealed that the arithmetic mean of delay time was 0.43 months in the eastern area, 0.87 months in the northern area, 10.93 months in the southern area, and 17.02 months in the western area. Although a few monitoring wells were strongly influenced by nearby pumping wells, the cross-correlation function of the groundwater level was the highest with precipitation in most wells. The seasonal autoregressive integrated moving average model indicated that the groundwater level will decrease in most wells in the western area and decrease or increase in different wells in the eastern area.

• Wind and Structures
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• 제20권6호
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• pp.763-791
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• 2015

"Wind and Ports" is a European project that has been carried out since 2009 to handle wind forecast in port areas through an integrated system made up of an extensive in-situ wind monitoring network, the numerical simulation of wind fields, the statistical analysis of wind climate, and algorithms for medium-term (1-3 days) and short term (0.5-2 hours) wind forecasting. The in-situ wind monitoring network, currently made up of 22 ultrasonic anemometers, provides a unique opportunity for detecting high resolution thunderstorm records and studying their dominant characteristics relevant to wind engineering with special concern for wind actions on structures. In such a framework, the wind velocity of thunderstorms is firstly decomposed into the sum of a slowly-varying mean part plus a residual fluctuation dealt with as a non-stationary random process. The fluctuation, in turn, is expressed as the product of its slowly-varying standard deviation by a reduced turbulence component dealt with as a rapidly-varying stationary Gaussian random process with zero mean and unit standard deviation. The extraction of the mean part of the wind velocity is carried out through a moving average filter, and the effect of the moving average period on the statistical properties of the decomposed signals is evaluated. Among other aspects, special attention is given to the thunderstorm duration, the turbulence intensity, the power spectral density and the integral length scale. Some noteworthy wind velocity ratios that play a crucial role in the thunderstorm loading and response of structures are also analyzed.