• 한국항공운항학회지
• /
• 제31권1호
• /
• pp.92-98
• /
• 2023

This paper used the golf course visitors' data in Jeju region to forecast the growth of inbound air traveler to Jeju. This is because the golf course visitors were proven to bring the highest economic and production inducement effect to the Jeju region. Based on such a data, this paper forecast the short-term growth rate of inbound air traveler using ARIMA to the Jeju until December 2025. According to ARIMA (0,1,0) (0,1,1) model, it was analyzed that the monthly number of golf course visitors to Jeju has been increasing steadily even since COVID-19 pandemic and the number is expected to grow until the end of 2025. Applying the same parameters of ARIMA (0,1,0) (0,1,1) to inbound air travel data, it was found the growth rate of inbound air travelers would be higher than the growth rate of 2019 shortly without moderate variation even though the monthly number of inbound travelers to Jeju had been dropped during COVID-19 pandemic.

• 대한토목학회논문집
• /
• 제7권1호
• /
• pp.111-120
• /
• 1987

부족량의 지속기간에 따른 성질을 관측하여, 다년간 계속되는 가뭄의 크기와 심도에 관한 빈도분석 방안을 개발하였다. 평균 부족량의 변화를 식별하기 위하여, 월 부족량의 통계치에 의한 표준화와 자료의 통합과정이 시행되었다. 가뭄의 크기와 심도에 관한 매개변수를 추정하기 위하여, Gamma 분포함수의 재생산성이 부족량에 대하여 적용되었다. 이들 분포와 지속기간 분포와의 복합화 맞 연구 결과가 실시간 예측에 관하여 의미하는 바를 논의하였다.

• 유통과학연구
• /
• 제13권2호
• /
• pp.15-24
• /
• 2015

Purpose - Foreign exchange risk control is in an important component in the international supply chain management. This study shows the importance of the reference period in forecasting future exchange rates with a specific illustration of KIKO currency option contracts, and suggests feasible preventive measures. Research design, data, and methodology - Using monthly Won-Dollar exchange rate data for January 1995~July 2007, I evaluate the statistical characteristics of the exchange rate for two sub-periods; 1) a shorter period after the East Asian financial crisis and 2) a longer period including the financial crisis. The key instrument of analysis is the basic normal distribution theory. Results - The difference in the reference period could lead to an unexpected development in contract implementation and a consequent financial loss. We may avoid foreign exchange loss by using derivatives such as forwards or currency options. Conclusions - We should consider not only level values but also the volatilities of financial variables in making a binding financial contract. Appropriate measures may differ depending on the specific supply chain pattern. We may extend the study with surveys on actual risk measures.

• 대기
• /
• 제18권2호
• /
• pp.83-95
• /
• 2008

In this study we have investigated the preceding eighteen large-scale climate indices with a lead time from zero to twelve months that have an influence on the variability of temperature and precipitation in Korea in order to understand which climate indices are overall available as predictors for long-range forecasting. We also have studied the dynamic link between preceding large-scale climate indices and regional climate using singular value decomposition analysis (SVDA) and correlation analysis (CA). Based on the coupled mode between large-scale circulation and regional climate, and correlation pattern between the preceding large-scale climate indices and large-scale circulation, the level of significance on climate indices as a predictor for monthly mean temperature and precipitation was evaluated for 5 and 1% level.

• 태양에너지
• /
• 제20권3호
• /
• pp.21-30
• /
• 2000

It is necessary to estimate the regression coefficients in order to predict the monthly mean daily global radiation on a horizontal surface. Therefore many different equations have proposed to evaluate them for certain areas. In this work, a new correlation has been made to predict the solar radiation for any area over Korea by estimating the regression coefficients taking into account percentage of possible sunshine, and cloud cover. Particularly, the multiple linear regression model proposed shows reliable results for estimating the global radiation with average deviation of -1 to 3 % from the measured values.

• Communications for Statistical Applications and Methods
• /
• 제25권6호
• /
• pp.659-671
• /
• 2018

In this study, we consider the extension of the heterogeneous autoregressive (HAR) model for realized volatility by incorporating a neural network (NN) structure. Since HAR is a linear model, we expect that adding a neural network term would explain the delicate nonlinearity of the realized volatility. Three neural network-based HAR models, namely HAR-NN, $HAR({\infty})-NN$, and HAR-AR(22)-NN are considered with performance measured by evaluating out-of-sample forecasting errors. The results of the study show that HAR-NN provides a slightly wider interval than traditional HAR as well as shows more peaks and valleys on the turning points. It implies that the HAR-NN model can capture sharper changes due to higher volatility than the traditional HAR model. The HAR-NN model for prediction interval is therefore recommended to account for higher volatility in the stock market. An empirical analysis on the multinational realized volatility of stock indexes shows that the HAR-NN that adds daily, weekly, and monthly volatility averages to the neural network model exhibits the best performance.

• 한국수자원학회:학술대회논문집
• /
• 한국수자원학회 2022년도 학술발표회
• /
• pp.304-304
• /
• 2022

가뭄은 인간 활동과 생태계의 다양한 측면에 영향을 미치는 중요한 자연재해 중 하나이다. 가뭄을 사전에 예측하여 필요한 완화 조치를 취하고 환경적 피해를 줄이는 것이 중요하다. 이에 따라 다양한 인공지능 기술을 이용한 가뭄 예측은 수문학, 수자원 관리, 농업 등의 분야에서 중요성이 커지고 있다. 최근에는 딥러닝 알고리즘을 기반으로 하는 중장기 강수예보를 위한 다양한 방법이 제시되고 있다. 이 논문의 목적은 가뭄 예보를 목적으로 월 강수량 예측을 위한 딥러닝 모델의 성능을 평가하는 것이다. 이를 위해 딥러닝 모델인 LSTM(Long Short-Term Memory)을 적용하였으며, 1981-2020년 기간의 월 강수 자료가 모델을 구축하기 위해 사용되었다. 관측자료를 기반으로 학습된 모델을 이용하여 테스트 기간에 대해 월 강수량을 예측하였다. 예측된 강수량을 통해 표준강수지수(Standardized Precipitation Index, SPI)을 산정하고, 예측 정확도를 분석하였다. 이 연구는 가뭄 예보를 위한 딥러닝 모델의 적용 가능성을 보여준다.

• KIEAE Journal
• /
• 제16권3호
• /
• pp.137-143
• /
• 2016

Purpose: Apartment housing should conduct a cyclic repair to keep and maintain the building performance since they are constructed. Therefore, the repair plan would be provided for long term period which explains the repair time, items and repair cost. Residents of apartment housing are responsible to pay for the repair activities. For repair cost, residents would reserve the money for repair little by little continuously until the required repair time because the repair cost takes a big burden for residents and lots of money a time. But, there is no systematic approach to provide the long term repair cost because it is no proper forecast of the repair cost to the upcoming repair time. In this study, it aimed at providing the monthly accumulation of the long term repair cost with the survey data in Seoul. Method: For these, the surveyed data are classified into 6 categories and number of data are 1,918. In addition, it developed the repair cost model for the 24 repair works and the cumulation function which is reflected with the each cost model. Result: This study are shown as follows : First, among the various estimation for the repair cost, the power function has a goodness of fit in statistics. Second, the monthly accumulation would be 12,840 won/household in size of $100,000m^2$ management area and $81.7won/m^2$ in size of the 1,000 household number during 40 years.

• 대기
• /
• 제25권4호
• /
• pp.669-683
• /
• 2015

In this study, we investigated the prediction skills of four multiple linear regression methods for monthly air temperature over South Korea. We used simulation results from four regional climate models (RegCM4, SNURCM, WRF, and YSURSM) driven by two boundary conditions (NCEP/DOE Reanalysis 2 and ERA-Interim). We selected 15 years (1989~2003) as the training period and the last 5 years (2004~2008) as validation period. The four regression methods used in this study are as follows: 1) Homogeneous Multiple linear Regression (HMR), 2) Homogeneous Multiple linear Regression constraining the regression coefficients to be nonnegative (HMR+), 3) non-homogeneous multiple linear regression (EMOS; Ensemble Model Output Statistics), 4) EMOS with positive coefficients (EMOS+). It is same method as the third method except for constraining the coefficients to be nonnegative. The four regression methods showed similar prediction skills for the monthly air temperature over South Korea. However, the prediction skills of regression methods which don't constrain regression coefficients to be nonnegative are clearly impacted by the existence of outliers. Among the four multiple linear regression methods, HMR+ and EMOS+ methods showed the best skill during the validation period. HMR+ and EMOS+ methods showed a very similar performance in terms of the MAE and RMSE. Therefore, we recommend the HMR+ as the best method because of ease of development and applications.

• 한국수자원학회논문집
• /
• 제38권6호
• /
• pp.471-483
• /
• 2005

일단위 강우-유출모형인 SSARR모형을 이용하여 한강, 낙동강, 섬진강유역에 월 앙상블 유량예측 시스템을 구축하였다. 우선 SSARR모형의 월 평균 유출량에 대한 모의정확성을 평가한 결과 한강과 낙동강유역에서는 과소추정하는 경향이 뚜렷하였으며, 섬진강유역에서는 모의오차의 분산이 커 정확성 개선이 필요하였다. 최적선형 보정기법을 적용하여 SSARR모형의 모의유량을 보정한 결과, 섬진강을 제외한 한강과 낙동강유역의 검증지점에서는 모의 정확성이 크게 개선되었다. 또한 1998년부터 2003년까지 월 앙상블 유량예측을 실시하여 예측 정확성을 평가하였다. 한강과 낙동강유역에서 최적선형 보정기법을 이용할 경우 앙상블 유량예측 정확성이 크게 개선되었으나, 섬진강유역은 개선효과가 미비하였다.