• 해양환경안전학회지
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• 제19권6호
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• pp.612-620
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• 2013

본 연구는 기존의 회귀분석과는 달리 금융, 경제, 무역 등 다양한 분야의 수요 예측에 널리 적용되고 있는 시계열 분석 방법을 시도하였다. 인천항의 1996년 1월부터 2013년 6월까지 입항 척수 자료를 바탕으로 정상성 검증, 모형의 식별, 모수의 추정, 진단 과정을 거쳐 장래 해상교통량을 예측하였다. 2014년 1월부터 2015년 12월까지 예측한 결과 2월달의 교통량이 다른 달 보다 적게 예측된 반면, 1월달의 교통량은 다른 달 보다 많을 것으로 나타났다. 또한 인천항은 지수평활법 보다 ARIMA 모형이 적합하며, 계절에 따라 월별 교통량의 차이를 보이는 것을 알 수 있다. 본 연구는 시계열 분석으로 장래 교통량을 월별로 예측하였다는 점에서 의의가 있다. 또한 기존의 회귀분석으로 예측한 장래 해상교통량보다 시계열 분석으로 예측한 장래 해상교통량이 더 적합한 모형인 것으로 판단된다.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2012년도 춘계학술대회
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• pp.833-836
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• 2012

최대수요전력 관리 장치는 현재 사용전력을 모니터링하여 예측 전력을 계산해 수용가에서 설정한 목표전력을 초과하지 않게 부하를 제어하는 장치이다. 부하의 제어는 예측된 최대수요전력이 목표전력을 초과할 경우 경보를 발생하고 부하를 차단하는 방식을 사용하기 때문에 최대수요전력에 대한 정확한 예측이 중요하다. 전력 변동이 심한 수용가에서는 기존의 예측 방법을 사용할 경우 최대수요전력 관리가 안정적이지 못하다는 단점이 있다. 본 논문에서는 기존의 최대수요전력 예측 방법 및 지수평활방법을 살펴보고 칼만 필터를 사용한 예측 방법을 제안한다.

• Journal of the Korean Data and Information Science Society
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• 제20권1호
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• pp.117-124
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• 2009

시계열자료에 계절효과가 존재할 때 성공적인 수요예측을 위해 Winters 방법과 같은 다양한 통계적 방법이 존재지만 신상품과 같이 과거 매출자료가 충분하지 않을 경우 통계적 방법 적용에 한계가 존재한다. 본 연구논문은 신제품과 같이 과거 매출자료가 충분하지 않아 계절효과 등을 추정하기 어려울 때 누적자료를 활용한 통계적 예측방법을 제안한다. 제안된 통계적 방법은 회귀모형이론에 기초하고 있으며 이 방법의 유효성을 최근 화장품 매출자료를 이용하여 검증하였다.

• 전기학회논문지
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• 제61권12호
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• pp.1765-1773
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• 2012

The accuracy of load forecast is very important from the viewpoint of economical power system operation. In general, the weekdays' load demand pattern has the continuous time series characteristics. Therefore, the conventional methods expose stable performance for weekdays. In case of special days or weekends, the load demand pattern has the discontinuous time series characteristics, so forecasting error is relatively high. Especially, weekdays near the thanksgiving day and lunar new year's day have the mixed load profile characteristics of both weekdays and weekends. Therefore, it is difficult to forecast these days by using the existing algorithms. In this study, a new load forecasting method is proposed in order to enhance the accuracy of the forecast result considering the characteristics of weekdays and weekends. The proposed method was tested with these days during last decades, which shows that the suggested method considerably improves the accuracy of the load forecast results.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2018년도 추계학술발표대회
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• pp.362-364
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• 2018

Predicting network traffic volume has become a popular topic recently due to its support in many situations such as detecting abnormal network activities and provisioning network services. Especially, predicting the volume of the next upcoming traffic from the series of observed recent traffic volume is an interesting and challenging problem. In past, various techniques are researched by using time series forecasting methods such as moving averaging and exponential smoothing. In this paper, we propose a long short-term memory neural network (LSTM) based network traffic volume prediction method. The proposed method employs the changing rate of observed traffic volume, the corresponding time window index, and a seasonality factor indicating the changing trend as input features, and predicts the upcoming network traffic. The experiment results with real datasets proves that our proposed method works better than other time series forecasting methods in predicting upcoming network traffic.

• 디지털융복합연구
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• 제12권9호
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• pp.111-121
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• 2014

본 연구는 지난 20여년 간의 시계열 광고비 자료를 근거로 향후 5년 간 우리나라의 연도별 총 광고비와 6대 광고매체의 광고비를 계량적 통계 분석을 통하여 예측해 보고자 하였다. 제일기획에서 발간한 광고연감 자료를 사용하여 계량적 분석을 통해 추정한 결과, 2018년 우리나라의 총 광고비는 10조 8730억원을 기록할 것으로 전망되었다. 6대 매체별 광고비는 단순회귀법, 지수평활법, SUR회귀법 등 3가지 방법으로 예측하였다. 연구결과를 바탕으로 광고학계와 광고실무계에 어떤 시사점이 있는 가를 논의하였다는 점에서 연구의 가치가 있다고 하겠다.

• 복식
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• 제50권2호
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• pp.29-45
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• 2000

The object of this study is to predict the import demands for korean textile, textile products and clothing products. The analyzing method performs through demand prediction method is by using Exponential Smoothing Model and STATGRAPHICS. The result from the practice of study is as follows ; Textile import ratio is expected to be increased constantly and the portion of textile import in our national total import is precited to reach to 3.92% in 2003. The import of the textile product to textile will be increased to 33.12% in 2003. The import ratio of clothing product ratio is also estimated to increase annually, Import ratio of clothing-product in textile-product import reaching to total 6.42% (83.89% in 2000, 90.31% in 2003), the growth rate of clothing import will be much higher than that of clothing export. From 2000 to 2003 , textile import is precited to be 5.23%. The import of the textile product will be increased by 8.04%. The import of clothing product will reaches 11.21%, which would be the highest rate among the products under review. Also , it predicts the constant increase as a result of prediction in the nation's total amount of import including the import amount of textile, textile-product, and clothing product.

• 전기학회논문지
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• 제58권1호
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• pp.1-6
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• 2009

The traditional demand prediction was based on the technique wherein electric power corporations made monthly or seasonal estimation of electric power consumption for each area and subscription type for the next one or two years to consider both seasonally generated and local consumed amounts. Note, however, that techniques such as pricing, power generation plan, or sales strategy establishment were used by corporations without considering the production, comparison, and analysis techniques of the predicted consumption to enable efficient power consumption on the actual demand side. In this paper, to calculate the predicted value of electric power consumption on a short-term basis (15 minutes) according to the amount of electric power actually consumed for 15 minutes on the demand side, we performed comparison and analysis by applying a 15-minute interval prediction technique to the average and that to the time series analysis to show how they were made and what we obtained from the simulations.

• The Journal of Asian Finance, Economics and Business
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• 제9권10호
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• pp.1-13
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• 2022

This paper empirically explores the predicting ability of the newly proposed smooth transition (ST) time-varying combining forecast methods. The proposed method allows the "weight" of combining forecasts to change gradually over time through its unique feature of transition variables. Stock market returns from 7 countries were applied to Ad Hoc models, the well-known Generalized Autoregressive Conditional Heteroskedasticity (GARCH) family models, and the Smooth Transition Exponential Smoothing (STES) models. Of the individual models, GJRGARCH and STES-E&AE emerged as the best models and thereby were chosen for constructing the combined forecast models where a total of nine ST combining methods were developed. The robustness of the ST combining forecasts is also validated by the Diebold-Mariano (DM) test. The post-sample forecasting performance shows that ST combining forecast methods outperformed all the individual models and fixed weight combining models. This study contributes in two ways: 1) the ST combining methods statistically outperformed all the individual forecast methods and the existing traditional combining methods using simple averaging and Bates & Granger method. 2) trading volume as a transition variable in ST methods was superior to other individual models as well as the ST models with single sign or size of past shocks as transition variables.

• 유통과학연구
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• 제19권3호
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• pp.25-34
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• 2021

Purpose: The purpose of this study is to analyze the economic ripple effect(ERE) of logistics industry by construction of Trans-Korea Railway (TKR) and present policy measures to minimize the economic loss of South Korea (SK). Research design, data and methodology: As the analysis method, exponential smoothing was used for demand forecasting, Input-Output analysis was used to estimate the economic ripple effect coefficient, and scenario analysis was used to an efficient way to invest in TKR to minimize SK's economic losses. Results: 1) the production(logistics fares) of TKR for 10 years after its completion is about 11.42 trillion won in positive relations, and 26.89 billion won in negative relations. 2) the ERE of SK in positive relations is 24.32 trillion won in production inducement effect, 8.1 trillion won in value-added inducement effect, 3.54 trillion won in import inducement effect, and 70,930 persons in employment inducement effect. But the ERE was insufficient in the negative relations. 3) SK's efficient investment method is providing materials and equipment by SK and building the TKR by North Korea in positive inter-Korea relations. Conclusions: For the successful operation of TKR, international cooperation, legalization and stable peace settlement on the Korean Peninsula are required.