• 설비공학논문집
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• 제18권1호
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• pp.87-94
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• 2006

In this paper, we investigated a feasibility of applying highest and lowest temperatures of the next day forecasted from a meteorological observatory to operation of an air-conditioning system with thermal storage. First we investigated specific characteristics of the time series of forecasted temperatures and errors in Osaka from 1994 to 1996. Since the forecast error is not always small, it might be difficult to use the forecasted data without correction for the sizing and the control of the thermal storage system. On the other hand, the autocorrelation functions of the forecast errors decrease relatively slowly during high summer season when cooling thermal storage is required. Since the values of the autocorrelation function; for one day are larger than 0.4, not small, the forecast errors can be predicted by proper statistical analysis. Thus, the forecasted values of the highest temperatures for the next day were improved by using the stochastic time series models.

• 대기
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• 제29권4호
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• pp.463-480
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• 2019

This study classified heavy rain types from K-means clustering for the hourly relationship between rainfall intensity and cloud top height over the Korean peninsula, and then examined their statistical characteristics for the period of June~August 2013~2018. Total rainfall amount of warm-type events was 2.65 times larger than that of the cold-type, whereas the lightning frequency divided by total rainfall for the warm-type was only 46% of the cold-type. Typical cold-type cases exhibited high cloud top height around 16 km, large reflectivity in the upper layer, and frequent lightning flashes under convectively unstable condition. Phenomenally, the cold-type cases corresponded to cloud cluster or multi-cell thunderstorms. However, two warm-type cases related to Changma and typhoon were characterized by heavy rainfall due to long duration, relatively low cloud top height and upper-level reflectivity, and the absence of lightning under the convectively neutral and extremely humid conditions. This study further confirmed that the forecast skill of rainfall could be improved by applying correction factor with the overestimation for cold-type and underestimation for warm-type cases in the Local Data Assimilation and Prediction System (LDAPS) operational model (e.g., BIAS score was improved by 5%).

• 산경연구논집
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• 제4권1호
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• pp.15-21
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• 2013

Purpose - Our goal was to determine whether there is a relationship between actual profits' deviation from the profits expected in earnings per share's adjustment announcements and the degree of apparent earnings management in annual financial statements. Research design, data, and methodology - The samples consisted of 133 companies from ten industries. The companies were selected among those listed in the stock exchange, and their data were examined covering the two-year period from 2008 to 2010. Tests were conducted using a regression model and SPSS statistical software. Results - The findings indicate the following. There is no significantly positive relationship among the last earnings per share's adjustment forecast, the first earnings forecast per share, and earnings management. Moreover, the amount of the latest earnings per share's adjustment forecast relative to its first forecast is not associated with the companies' discretionary accruals items. Finally, the hypothesis that a relationship exists between companies' latest adjustments of their earnings per share and earnings management was tested the results indicate that there is no such relationship. Conclusions - The study's results suggest that the amount of earnings per share's adjustment is not a motivation for earnings management.

• 응용통계연구
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• 제31권2호
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• pp.229-239
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• 2018

본 논문에서는 시간적 계층 개념을 활용하여 시계열 자료를 예측하는 방법을 소개한다. 횡단적 계층 자료 분석에서와 유사한 방법으로 중복되지 않는 시간적 계층을 시계열 자료에 구조화할 수 있다. 이러한 시간적 계층을 활용하여 조정된 예측은 기존의 계층별 독립적 기저 예측 및 상향식 예측보다 더 정확하고 강건한 예측값을 생성한다. 실증 분석으로서 국내 교통사고 발생건수를 시간적 계층 개념을 활용하여 예측한다. 분석 결과, 조정 예측이 기존의 다른 예측보다 예측 성능면에서 더 우수함을 확인할 수 있다.

• 응용통계연구
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• 제30권1호
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• pp.181-193
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• 2017

본 논문에서는 계층적 시계열 자료 분석을 위한 대표적인 두 가지 방법인 상향식과 최적조합 예측법을 소개한다. 이러한 예측법은 계층적 시계열을 구성하는 모든 계열을 예측해야 하는 독립적 예측과 달리, 임의의 조정 과정이 없이 하위 계층 계열의 예측값의 합은 항상 상위 계층의 예측값과 일치하게 된다. 또한, 독립적 예측과 비교하여 예측력을 향상시킨다. 계층적 예측법의 효율성을 살펴보기 위하여 국내 16개 시도별 남녀 교통사고 발생건수 시계열 자료를 예측하였다. 이를 통하여 교통사고 발생건수에 대한 각 계층의 예측에서 계층적 방법과 독립적 방법의 차이점 및 우수성을 비교하였다.

• 수산경영론집
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• 제46권1호
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• pp.93-107
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• 2015

This study aims to analyze causalities among Hairtail prices by distribution channel using a vector autoregressive model. This study applies unit-root test for stability of data, uses Granger causality test to know interaction among Hairtail Prices by distribution channel, and employes the vector autoregressive model to estimate statistical impacts among t-2 period variables used in model. Analyzing results of this study are as follows. First, ADF, PP, and KPSS tests show that the change rate of Hairtail price by distribution channel differentiated by logarithm is stable. Second, a Granger causality test presents that the producer price of Hairtail leads the wholesale price and then the wholesale price leads the consumer price. Third, the vector autoregressive model suggests that the change rate of Hairtail producer price of t-2 period variables statistically, significantly impacts change rates of own, wholesale, and consumer prices at current period. Fourth, the impulse response analysis indicates that impulse responses of the structural shocks with a respectively distribution channel of the Hairtail prices are relatively more powerful in own distribution channel than in other distribution channels. Fifth, a forecast error variance decomposition of the Hairtail prices points out that the own price has relatively more powerful influence than other prices.

• Structural Engineering and Mechanics
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• 제54권2호
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• pp.221-237
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• 2015

An integrated method is proposed for structural nonlinear damage detection based on time series analysis and the higher statistical moments of structural responses in this study. It combines the time series analysis, the higher statistical moments of AR model residual errors and the fuzzy c-means (FCM) clustering techniques. A few comprehensive damage indexes are developed in the arithmetic and geometric mean of the higher statistical moments, and are classified by using the FCM clustering method to achieve nonlinear damage detection. A series of the measured response data, downloaded from the web site of the Los Alamos National Laboratory (LANL) USA, from a three-storey building structure considering the environmental variety as well as different nonlinear damage cases, are analyzed and used to assess the performance of the new nonlinear damage detection method. The effectiveness and robustness of the new proposed method are finally analyzed and concluded.

• 디지털융복합연구
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• 제12권3호
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• pp.237-242
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• 2014

IT 서비스 및 컴퓨팅 자원을 기반으로 인터넷 서비스를 제공하는 클라우드 컴퓨팅이 최근 큰 관심을 받고 있다. 그러나 클라우드 컴퓨팅 시스템에 저장되는 데이터는 암호화한 후 저장되어도 기밀 정보가 유출되는 문제점이 있다. 본 논문에서는 사용자가 클라우드 컴퓨팅 시스템에서 제공되는 데이터를 제 3자가 임의로 악용하는 것을 예방하기 위한 그룹 키 관리 프로토콜을 제안한다. 제안된 프로토콜은 임의의 사용자가 원격에서 클라우드 컴퓨팅 서버에 접근할 경우 서버에 존재하는 사용자 인증 데이터베이스내 사용자 정보를 일방향 해쉬 함수와 XOR 연산을 사용하여 사용자 인증을 제공받는다. 도한 사용자의 신분확인 및 권한을 연동하여 클라우드 컴퓨팅 시스템에 불법적으로 접근하는 사용자를 탐색함으로써 클라우드 컴퓨팅의 사용자 보안 문제를 해결하고 있다.

• 응용통계연구
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• 제37권3호
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• pp.297-309
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• 2024

본 논문에서는 자기회귀 신경망 모형과 지수평활법을 결합(NNARX+ETS 모형)하고 그 성능을 평가한다. 제안된 결합 모형은 시계열 자료를 예측하기 위하여 NNARX 모형의 외생변수로서 ETS 모형의 구성 성분을 활용한다. 이 모형의 주요 아이디어는, 신경망 모형이 원시계열 자료의 과거 시차만을 고려하는 것을 한계를 넘어서서 전통적 시계열 예측 방법인 지수평활법에 의해서 추출된 정제된 시계열 구성 성분까지도 추가로 신경망 모형의 입력값으로 사용하는 것이다. 예측 성능 평가는 2가지 실제 시계열 자료를 사용하였으며 제안된 모형을 NNAR 모형 및 전통적 시계열 분석 방법인 ETS와 ARIMA 모형과 비교하였다.

• The Plant Pathology Journal
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• 제35권6호
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• pp.585-597
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• 2019

A disease forecast model for Marssonina blotch of apple was developed based on field observations on airborne spore catches, weather conditions, and disease incidence in 2013 and 2015. The model consisted of the airborne spore model (ASM) and the daily infection rate model (IRM). It was found that more than 80% of airborne spore catches for the experiment period was made during the spore liberation period (SLP), which is the period of days of a rain event plus the following 2 days. Of 13 rain-related weather variables, number of rainy days with rainfall ≥ 0.5 mm per day (L_day), maximum hourly rainfall (P_max) and average daily maximum wind speed (W_avg) during a rain event were most appropriate in describing variations in airborne spore catches during SLP (S_i) in 2013. The ASM, Ŝ_i = 30.280+5.860×L_day×P_max-2.123×L_day×P_max×W_avg was statistically significant and capable of predicting the amount of airborne spore catches during SLP in 2015. Assuming that airborne conidia liberated during SLP cause leaf infections resulting in symptom appearance after 21 days of incubation period, there was highly significant correlation between the estimated amount of airborne spore catches (Ŝ_i) and the daily infection rate (R_i). The IRM, ${\hat{R}}_i$ = 0.039+0.041×Ŝ_i, was statistically significant but was not able to predict the daily infection rate in 2015. No weather variables showed statistical significance in explaining variations of the daily infection rate in 2013.