• 대한전기학회:학술대회논문집
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• 대한전기학회 2008년도 추계학술대회 논문집 전력기술부문
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• pp.83-85
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• 2008

The authors develop and compare the performance of short-term forecasting models on electricity market prices in Korea. The models are based on time-series methods. The outcome shows that the EGARCH model has the best results in the out-of-sample forecasts.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2011년도 제42회 하계학술대회
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• pp.590-591
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• 2011

This paper proposes a short-term load forecasting by using a temperature and load pattern. The forecasting model that represents the relations between load and temperature which get a numeral expected temperature based on the past temperature was constructed. Case studies were applied to load forecasting for 2009 data, and the results show its appropriate accuracy.

• 한국대기환경학회지
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• 제5권2호
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• pp.84-96
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• 1989

To evaluate the short term air pollution dispersion model, the diffusion experiment was conducted on the flat terrain near Chuncheon. Sulfur hexafluoride $(SF_6)$ gas was used to determine the horizontal spread of plume $(\sigmay)$ for calculated by CRSTER model. Results show that CRSTER model underestimates $\sigma$y because averaging time adjustment is not applied to calculate the $\sigma$y. The scheme that can estimate the atmospheric stability more accurate than Turner method, was presented.

• Communications for Statistical Applications and Methods
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• 제19권6호
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• pp.869-876
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• 2012

In this paper, we applied seasonal time series models such as ARIMA, FARIMA, AR-GARCH and Holt-Winters in consideration of seasonality to forecast short-term electricity demand data. The results for performance evaluation on the time series models show that seasonal FARIMA and seasonal Holt-Winters models perform adequately under the criterion of Mean Absolute Percentage Error(MAPE).

• 전기의세계
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• 제31권5호
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• pp.368-374
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• 1982

This paper describes a combined algorithm for short-term-load forecating. One of the specific features of this algorithm is that the base, weather sensitive and residual components are predicted respectively. The base load is represented by the exponential smoothing approach and residual load is represented by the Box-Jenkins methodology. The weather sensitive load models are developed according to the information of temperature and discomfort index. This method was applied to Korea Electric Company and results for test periods up to three years are given.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1994년도 추계학술대회 논문집 학회본부
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• pp.24-26
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• 1994

This paper describes a numerical model for the short-term operation strategy of the cogeneration systems. Especially this paper considered various auxiliary equipments used for the effective operation of cogeneration system. Minimum daily operation costs of topping cycle are calculated by using LP. Simulation results of some cases are analyzed and compared each other. Through these simulations the validity of the proposed model considered various auxiliary equipments is verified.

• 산업경영시스템학회지
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• 제41권1호
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• pp.50-58
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• 2018

Intermittent demand is a demand with a pattern in which zero demands occur frequently and non-zero demands occur sporadically. This type of demand mainly appears in spare parts with very low demand. Croston's method, which is an initiative intermittent demand forecasting method, estimates the average demand by separately estimating the size of non-zero demands and the interval between non-zero demands. Such smoothing type of forecasting methods can be suitable for mid-term or long-term demand forecasting because those provides the same demand forecasts during the forecasting horizon. However, the smoothing type of forecasting methods aims at short-term forecasting, so the estimated average forecast is a factor to decrease accuracy. In this paper, we propose a forecasting method to improve short-term accuracy by improving Croston's method for intermittent demand forecasting. The proposed forecasting method estimates both the non-zero demand size and the zero demands' interval separately, as in Croston's method, but the forecast at a future period adjusted by binomial weight according to occurrence probability. This serves to improve the accuracy of short-term forecasts. In this paper, we first prove the unbiasedness of the proposed method as an important attribute in forecasting. The performance of the proposed method is compared with those of five existing forecasting methods via eight evaluation criteria. The simulation results show that the proposed forecasting method is superior to other methods in terms of all evaluation criteria in short-term forecasting regardless of average size and dispersion parameter of demands. However, the larger the average demand size and dispersion are, that is, the closer to continuous demand, the less the performance gap with other forecasting methods.

• 한방재활의학과학회지
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• 제26권3호
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• pp.129-141
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• 2016

Objectives As awareness of the public about Korean medicine health care and the social demand about improvement for quality of health care service is constantly rising, the quality evaluation of Korean medicine health care service is needed to improve the quality. Through trial of Delphi method, we tried to set the priority in short, medium, long term among the disease which is the subject of quality assessment. Methods Carrying out the delphi survey to 50 experts of korean medicine who were recommended by the 41 member societies of Korean medicine and related organizations, we selected final candidates for quality assessment. It is composed with total 2 rounds, and we investigated the priority in three aspects; the importance of the matter, possibility quality assessment, potential about if there's any chance of improvement. Results By delphi method, we set the priority of quality assessment. Base on the result of the second round, we classified importance of the questions into above average, average, below average, and categorized items as short, medium, long term according on the final priority. We classified of musculoskeletal diseases and diseases of connective tissues and musculoskeletal injury as short term and cerebrovascular disease and disease of nerve system and malignant neoplasm as medium term, disease of digestive organs and diseases, symptoms and abnormal findings in clinical field or inspections which are not categorized as long term. Conclusions We set the subjects of quality assessment by delphi survey by experts, and classified into short, medium, long term. Further research is necessary for execution the Quality Assessment to each of the candidate. Also, we can send feedback to medical institution base on the result of Quality Assessment. then it would be able to induce the improvement in quality of medical institution by itself.

• 지역사회간호학회지
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• 제20권2호
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• pp.251-258
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• 2009

Purpose: The study aimed to compare characteristics associated with smoking and smoking cessation of those who had succeeded in smoking cessation. Methods: Data were collected from January to June, 2008. The subjects were 9,819 smokers who were registered at the smoking cessation clinic of public health centers in Incheon. Four characteristics (demographic, health promotion, smoking, smoking cessation) were compared between 6-week (short-term) and 6-month (long-term) success groups. Results: There was a significant difference between the 6-week and 6-month success groups for smoking cessation in demographic characteristics (gender, age, job, social security), health promotion (BMI, alcohol dependency, BP), smoking (first smoking age, smoking duration, expiration CO concentration, nicotine dependency), and smoking cessation (attempt to quit smoking, reason for smoking cessation, information source for registration). Conclusion: The group of short-term smoking cessation success was younger than the other. Also, short-term success group was of lower socioeconomic class than the other. The 6-month success group had a larger number of attempts to quit smoking. Therefore, smoking cessation policy should be focused more on younger people and those in lower socioeconomic status. These groups should be given advice on smoking cessation motives and more frequent counseling for smoking cessation.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2020년도 학술발표회
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• pp.101-101
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• 2020

Traditional stochastic simulation of hydroclimatological variables often underestimates the variability and correlation structure of larger timescale due to the difficulty in preserving long-term memory. However, the Long Short-Term Memory (LSTM) model illustrates a remarkable long-term memory from the recursive hidden and cell states. The current study, therefore, employed the LSTM model in stochastic generation of hydrologic and climate variables to examine how much the LSTM model can preserve the long-term memory and overcome the drawbacks of conventional time series models such as autoregressive (AR). A trigonometric function and the Rössler system as well as real case studies for hydrological and climatological variables were tested. Results presented that the LSTM model reproduced the variability and correlation structure of the larger timescale as well as the key statistics of the original time domain better than the AR and other traditional models. The hidden and cell states of the LSTM containing the long-memory and oscillation structure following the observations allows better performance compared to the other tested conventional models. This good representation of the long-term variability can be important in water manager since future water resources planning and management is highly related with this long-term variability.