• The Journal of Asian Finance, Economics and Business
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• 제8권8호
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• pp.647-658
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• 2021

Analysts' forecasts are important for providing useful guidance to investors, especially individual or small investors, and therefore it becomes critical to identify the elements which can potentially increase errors in analysts' forecasts. This study investigates potential factors which can lead to errors in forecasting by analysts, specifically in terms of the level and attributes of corporate earnings. Utilizing a sample of firms listed on the Korean stock markets, this study provides evidence that firms with more volatile and unpredictable earnings feature less accurate analyst forecasts. This study fills a void in the literature by conducting empirical tests for earnings attributes in terms of volatility and unpredictability that could potentially undermine the forecast accuracy. The negative association between the quality of earnings and forecast accuracy is more pronounced for firms with negative net income values. Additional analysis demonstrates that forecast accuracy is significantly lower for the fourth quarter than for other fiscal quarters and that fourth quarter earnings tend to be more volatile and unpredictable. This study contributes to the literature by providing new empirical evidence regarding the comprehensive effects of earnings quality and level on analysts' forecasting accuracy and further suggests potential factors contributing to the fourth quarter anomaly in analyst forecasts in terms of earnings attributes.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1997년도 하계학술대회 논문집 D
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• pp.1177-1179
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• 1997

In this paper, short-term power demand forecast using exclusion of week periodicity presented. Week periodicity excluded from weekday change ratio. Forecast term of five and multiple regression model of the three form was composed. Forecast result was good. Therefore, It Could be the power demand forecast of special day(weekend). This method may contribute improvement of forecast accuracy.

• 응용통계연구
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• 제35권5호
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• pp.645-655
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• 2022

본 논문에서는 R에서 시계열 자료 예측을 위한 자동화 함수에 대하여 고찰하고 그 예측 성능을 비교합니다. 대표적인 시계열 예측 방법인 지수 평활 모형과 ARIMA (autoregressive integrated moving average) 모형을 대상으로 하였으며, 이들의 모형화 및 예측 자동화를 가능하게 하는 R의 4가지 자동화 함수인 forecast::ets(), forecast::auto.arima(), smooth::es()와 smooth::auto.ssarima()를 대상으로 하였습니다. 이들의 예측 성능을 비교하기 위하여 3,003가지의 시계열로 구성되어 있는 M3-Competition자료와 3가지의 정확성 척도를 사용하였습니다. 4가지 자동화 함수는 모형화의 다양성 및 편리성, 예측 정확도 및 실행 시간 등에서 각자 장단점이 있음을 확인하였습니다.

• 경영과학
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• 제30권1호
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• pp.91-102
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• 2013

This study has an aim to analyze the effects of ADS on conjunctivitis patients among the residents of Seoul, Korea, between 2005 and 2008. For this purpose, the number of medical services provided to conjunctivitis patients on the days of windblown dust storms and the days without any windblown dust storms were analyzed by conducting paired t-test. The interactive effects of the ADS density and the accuracy of ADS forecast on the fluctuation of conjunctivitis cases were also investigated. The results showed that, even with an accurate forecast issued 24 hours prior to the event, the average number of medical services provided for conjunctivitis was higher on the index days than the comparison days. On the other hand, in cases of failure to provide an accurate forecast 24 hours prior to the ADS event, the number of conjunctivitis attacks reported was statistically significantly higher on the index days for 3~5 days after the occurrence of a dust storm in relation to the comparison days. We also found that the rate of increase in asthma treatments on the index days with low level of $PM_{10}$ concentration rather than high $PM_{10}$ level was more significant for all lag days. This study provides evidence that ADS events are significantly associated with conjunctivitis symptoms and the failure to forecast ADS events with low $PM_{10}$ level might aggravate conjunctivitis disease.

• 한국농공학회지
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• 제41권6호
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• pp.25-32
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• 1999

The purpose of this study is to analyse the accuracy of weather forecasts of temperature, precipitation probability , and sky condition and to evaluate the applicability of weather forecasts for the estimation of potential evapotranspiration for irrigation scheduling. Five weather station s were selected to compare forecasted and measured climatcal data. The error between forecasted and measured temperature was calculated and discussed. The accuracy of temperature forecast using relative frequency of the error was calculated . The temperature forecasting showed considerably high accuracy. Average sunshine hours for forecasted sky conditions were calculated and showed reasonable quality. From the reliability graphs, the forecasting precipation probabililty was reliable. Potential evapotranspirations were calculated and compared using forecast and measured temperatures. The weather forecast is considered usable for irrigation scheculing.

• 환경위생공학
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• 제24권3호
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• pp.37-54
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• 2009

The study has analyzed impacts and intensity of weather that affect $PM_{10}$ concentration based on PM10 forecast conducted by the city of Seoul in order to identify ways to improve the accuracy of PM10 forecast. Variables that influence $PM_{10}$ concentration include not only velocity and direction of the wind and rainfalls, but also those including secondary particulate matter, which were identified to greatly influence the concentration in complicated manner as well. In addition, same variables were found to have different impacts depending on seasons and conditions of other variables. The study found out that improving accuracy of $PM_{10}$ concentration forecast face some limits as it is greatly influenced by the weather. As an estimation, this study assumed that basic research units and artificially estimated pollutant emissions, study on mechanisms of secondary particulate matter productions, observatory compliment, and enhanced forecaster's expertise are needed for better forecast.

• 한국조사연구학회지:조사연구
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• 제10권2호
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• pp.71-96
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• 2009

본 연구는 1980년대 이후부터 2000년대 초반까지 우리나라에서 이루어진 과거 인구추계의 정확성을 분석하였다. 인구추계의 정확성 평가대상으로는 총인구와 연령대별 인구뿐만 아니라 합계출산율과 기대수명과 같은 인구변동 요인들 또한 검토하였다. 총인구 예측의 정확성과 관련하여 전반적인 분석결과는 우리나라 과거 인구추계에서 정확성 향상의 뚜렷한 패턴이 관측되지 않음을 보여 주었다. 연령대별 예측의 경우 연소 인구와 노인 인구의 예측에서 상대적으로 큰 오차가 발생하였으며, 생산가능인구의 예측은 상대적으로 정확성이 높은 것으로 나타났다. 인구변동 요인들에 대한 예측의 경우 전반적으로 합계출산율은 과대 추정의 문제를 그리고 기대수명의 경우 과소 추정의 문제를 지속적으로 보였다. 분석 결과는 또한 인구변동 요인들 중 합계출산율 예측에서 발생한 오차가 기대수명 예측에서 발생한 오차에 비해 큰 것으로 나타남으로써 행동적 요소의 영향을 강하게 받는 변수의 경우 예측에 있어서 상대적으로 큰 어려움이 있음을 시사하고 있다.

• 한국태양에너지학회 논문집
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• 제39권3호
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• pp.59-66
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• 2019

New and renewable energy forecasts are key technology to reduce the annual operating cost of new and renewable facilities, and accuracy of forecasts is paramount. In this study, we intend to build a model for the prediction of short-term solar power generation for 1 hour to 3 hours. To this end, this study applied two time series technique, ARIMA model without considering seasonality and SARIMA model with considering seasonality, comparing which technique has better predictive accuracy. Comparing predicted errors by MAE measures of solar power generation for 1 hour to 3 hours at four locations, the solar power forecast model using ARIMA was better in terms of predictive accuracy than the solar power forecast model using SARIMA. On the other hand, a comparison of predicted error by RMSE measures resulted in a solar power forecast model using SARIMA being better in terms of predictive accuracy than a solar power forecast model using ARIMA.

• 한국군사과학기술학회지
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• 제21권4호
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• pp.529-540
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• 2018

As the equipment of the military has recently become more sophisticated and expensive, the cost of purchasing spare parts is also steadily increasing. Therefore, demand forecast accuracy is also becoming an issue for the effective execution of the spare parts budget. This study predicts the demand by using the data of spare parts consumption of the KF-16C fighter which is being operated in the Republic of Korea Air Force. In this paper, SARIMA(Seasonal Autoregressive Integrated Moving Average) is applied to seasonal data after dividing the spare parts consumptions into seasonal data and non-seasonal data. Proposing new methods, Majority Voting and Hybrid Method, to the non-seasonal data which consists of spare parts of low consumption with unclear pattern, We want to prove that the demand forecast accuracy of spare parts improves.

• 한국수자원학회논문집
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• 제50권8호
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• pp.537-549
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• 2017

본 연구에서는 기상청에서 제공하는 국지예보모델(LDAPS)과 일본 기상청의 중규모모델(Meso-Scale Model, MSM)을 이용하여 태풍 및 정체전선 등 3개의 강우사상과 남강댐 유역 내 산청 유역에 대해 강우 및 홍수 예측 정확도를 평가하고 비교 검토하였다. 강우예측 정확도 평가 결과, LDAPS와 MSM 모두 태풍 사상과 같은 광역적인 예측에 대해서는 예측 정확도가 높은 것으로 나타났으나, 정체전선과 같이 국지적으로 발생하는 강우사상의 경우 예측 오차가 많이 발생하는 것으로 나타났다. 홍수예측 정확도 평가 결과, 선행시간이 증가함에 따라 점점 예측 정확도가 향상되는 것을 확인할 수 있었으며, LDAPS와 MSM 모두 기상 및 수자원간의 연계를 통하여 강우 및 홍수 예측 분야에서의 활용 가능성을 확인할 수 있었다.