• 한국산학기술학회논문지
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• 제12권5호
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• pp.2261-2266
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• 2011

초음파 컬러 유동 사상에서 가장 많이 사용되는 Kasai 알고리듬은 래그-1 자기상관 방법으로서 적은 계산량으로 비교적 우수하게 도플러 평균주파수를 추정한다. 하지만 특히 깊은 곳을 영상화하는 경우 낮은 신호 대 잡음비로 인해 추정성능이 저하된다. 본 논문에서는 낮은 신호 대 잡음비에서도 Kasai 알고리듬보다 우수한 디에일리어스된 래그-2 자기상관방법을 제안하고 시뮬레이션을 통해 성능을 검증하였다. 제안한 방법은 잡음이 존재하는 경우 도플러 평균주파수 추정 성능을 평균 자승 오차 측면에서 전반적으로 약 2~3dB 정도 개선시켜줌을 확인하였다.

• 한국지하수토양환경학회:학술대회논문집
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• 한국지하수토양환경학회 2004년도 총회 및 춘계학술발표회
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• pp.455-458
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• 2004

This study uses time series analyses to evaluate fluctuation of water levels in a geothermal water well due to pumping, in relation to rainfall at Dongrae hot-spring site on the southeastern coast of tile Korean peninsula. The volume of water pumped from the public study wells ranges from 542 to 993 m$^3$/month, and the minimum water level ranged from 35 to 144.7 m during the measured period. Autocorrelation analysis was conducted for the withdrawal rate at the public wells, water levels and rainfall. The autocorrelation of the withdrawal rate shows distinct periodicity with 3 months of lag time, the autocorrelation of rainfall shows weak linearity and short memory with 1 months of lag time, and the autocorrelation of water levels shows weak linearity and short memory with 2 months of lag time. The cross-correlation between the pumping volume and the minimum water level shows a maximum value 1 at a delayed time of 34 months. The cross-correlation between rainfall and the minimum water level shows a maximum value of 0.39 at a delayed time of 32 months.

• Journal of the Korean Statistical Society
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• 제17권1호
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• pp.24-29
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• 1988

The asymptotic distribution of the sample partial autocorrelation terms after lag p of an AR(p) model has been shown by Dixon(1944). The derivation is based on multivariate analysis and looks tedious. In this paper we present an interesting contour-integral derivation.

• 한국환경보건학회지
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• 제14권1호
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• pp.39-45
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• 1988

The stochastic variations were analyzed periodicity by autocorrelation, variance spectrum and Fourier series. These time series included hourly and hourly mean observations on DO, water temperature and air temperature which measured by automatic recording instrument at Guii from 1, Jan., 1986 to 23, Feb., 1986. The results of study were as follows: l. Autocorrelation coef. (lag time 120) DO($\varrho_1$= 0.9705), WT($\varrho_1$ = 0.9890), and AT($\varrho_1$ = 0.9874) were deeply related. DO and AT clearly showedr 24-hour periodicities while WT showed 23-26 hour periodicity. 2. Spectral density showed high at 24 hour in eech item and all of them showed weak peak at 12 hour. 3. The explained variance, which was a measure of the contribution of periodic function to the original time series, varied high 90.8 - 94.7%. This results showed that water qualities at Guii were affected deterministic components.

• The Journal of Asian Finance, Economics and Business
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• 제9권9호
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• pp.1-8
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• 2022

This paper studies market efficiency from a weak form aspect using opening and closing prices of the Shanghai stock exchange composite index (SSEC) and Shenzhen stock exchange composite index (SZSEC) under the expected return theory. Classical methods (autocorrelation and runs test) are used to examine the features of stock returns, and little evidence against mutual independence of returns is found. We predict daily returns of SSEC and SZSEC with AR(p) and VAR(p) models (in this paper, p = 5 is taken as a one-week lag) and perform a virtual experiment on two indexes based on the predicted value of daily returns from AR(p) or VAR(p) model. From the results of AR(p) and VAR(p) for two indexes, we attempt to find out how the market efficiency level changes when the information from the other market is under consideration as we check the market efficiency level in one market. We find that SSEC in 2014-2016 and SZSEC in 2015-2016 are inefficient from the result of autocorrelation, that SSEC in 2016 and SZSEC in 2013 are not efficient from the result of runs test, that the stock market is efficient except 2005, 2009, 2010 and 2017 in SSEC and 2005, 2016 and 2017 in SZSEC and that SSEC is more influenced by SZSEC but SSEC influences SZSEC less from the result of the virtual experiment.

• 한국지하수토양환경학회:학술대회논문집
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• 한국지하수토양환경학회 2004년도 총회 및 춘계학술발표회
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• pp.447-450
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• 2004

This study was conducted to characterize groundwater and river-water fluctuations at a riverbank filtration site in Daesan-myeon adjacent to the Nakdong River, using time series analysis. Water levels from six observation wells from January 2003 to October 2003 were measured. The autocorrelation analysis indicates that the wells are divided into three groups: group 1 represents strong linearity and memory, group 2 intermediate linearity and memory, and group 3 weak linearity and memory. The analysis indicates that groundwater levels in different monitoring wells vary in response to river-water levels, groundwater withdrawal and seasonal rainfall. Cross-correlation was also divided into three groups. Group 1 shows the highest cross-correlation function (0.49 - 0.54) for a lag time of 0 hours, group 2 intermediate cross-correlation function (0.34 - 0.45), and group 3 the lowest cross-correlation function (0.23 - 0.25). Different cross-correlation functions among the 3 groups are interpreted as an effect of tile distance from the river to the pumping wells.

• Journal of Preventive Veterinary Medicine
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• 제41권2호
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• pp.79-83
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• 2017

In this study, we used a choropleth map to explore the spatial variation of the risk of cattle herds being bovine tuberculosis (BTB) positive in Gangwon-do in 2015. The map shows that the risk of being BTB-positive was lower in provinces located in the middle of Gangwon-do (Wonju, Youngwol, Peongchang, and Kangneung) than in other provinces. In addition, one province located in the north (Goseong) had a low risk of BTB. The estimate for the intercept of the spatial lag model was 0.66, and the spatial autocorrelation coefficient (lambda) was 0.20 (Table 1). The Moran's I was 0.33 with p-value of 0.02. In 2015, provinces located in the North West (Hwacheon) and East (Donghae) of Gangwon-do had a higher BTB risk. We identified some specific provinces at low BTB-positive risk, information that may prove useful for control of BTB in the study area.

• 한국ITS학회 논문지
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• 제20권1호
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• pp.54-69
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• 2021

도로교통법이 개정되며 개인형 이동수단(특히, 전동킥보드) 이용에 대한 정책적인 개선방안이 제시되고 있다. 하지만 많은 기기들이 보도 위에 방치되는 등 이용상의 문제점을 해결하고자 하는 논의는 부족한 실정이다. 이에 따라 본 연구에서는 서울시를 200m 격자로 구분하여 공유 전동킥보드의 대여량과 반납량에 영향을 미치는 요인을 분석하고자 한다. 특정공간을 기준으로 집계된 자료의 특성을 반영하기 위해 공간자기상관모형인 공간시차모형과 공간오차모형, 공간더빈모형, 공간더빈오차모형을 구축하였으며, 최종모형으로 공간더빈모형을 선정하였다. 영향요인 분석결과, 인구지표, 토지이용지표, 교통시설지표가 통계적으로 유의하게 영향을 미치는 것으로 분석되었다. 본 연구의 결과는 평일과 주말의 이용특성을 고려한 효율적인 운영방안을 위한 기초자료로 활용될 수 있을 것으로 기대된다.

• Environmental Engineering Research
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• 제22권3호
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• pp.302-311
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• 2017

Nowadays, with the burgeoning development of economy, $CO_2$ emissions increase rapidly in China. It has become a common concern to seek effective methods to forecast $CO_2$ emissions and put forward the targeted reduction measures. This paper proposes a novel hybrid model combined principal component analysis (PCA) with regularized extreme learning machine (RELM) to make $CO_2$ emissions prediction based on the data from 1978 to 2014 in China. First eleven variables are selected on the basis of Pearson coefficient test. Partial autocorrelation function (PACF) is utilized to determine the lag phases of historical $CO_2$ emissions so as to improve the rationality of input selection. Then PCA is employed to reduce the dimensionality of the influential factors. Finally RELM is applied to forecast $CO_2$ emissions. According to the modeling results, the proposed model outperforms a single RELM model, extreme learning machine (ELM), back propagation neural network (BPNN), GM(1,1) and Logistic model in terms of errors. Moreover, it can be clearly seen that ELM-based approaches save more computing time than BPNN. Therefore the developed model is a promising technique in terms of forecasting accuracy and computing efficiency for $CO_2$ emission prediction.

• The Journal of Asian Finance, Economics and Business
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• 제9권1호
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• pp.167-176
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• 2022

By analyzing the impact of oil prices on economic growth, this study has shown a new insight into the link between oil price inflation and economic growth. The primary goal of this study is to determine if oil prices are pro-growth or anti-growth. To provide empirical proof, the series data for both the core and control variables from 1972 to 2020 was used to justify the association on empirical grounds. To account for the presence of a unit root, the Augmented Dickey-Fuller Test was used, and after making the series compatible for co-integration, the Autoregressive distributed lag model was used to determine the empirical estimate. Additionally, the empirical models were used to diagnose heteroscedasticity and autocorrelation. The reference point model reveals that in developing nations like Pakistan, economic growth is anti-growth with an increase in prices, and it responds negatively to economic growth in the long and short run. As a result, oil price inflation in Pakistan fails to have a significant beneficial impact on economic growth in both the long and short run, but it does raise the general price level in the economy.