• Journal of Korean Institute of Industrial Engineers
• /
• v.38 no.3
• /
• pp.208-219
• /
• 2012

As the number of end-of-life vehicles (ELVs) has kept increasing, the management of ELV has also become one of the academic research focuses and European Union recently adopted the directive on ELVs. For the stakeholders has become a principle agent of dealing with all about ELVs, it is relevant investment decision to set up and to decide high-cost ELVs entity locations and to forecast future ELVs' amount in advance. In this paper, transition probability matrixes between months are made by using Markov Chain and the number of ELVs is predicted with them. This study will perform a great role as a fundamental material in Korea where just started having interests about recycling resources and studies related to the topic. Moreover, the forecasting method developed for this research can be adopted for other enhancements in different but comparable situations.

• Korean Journal of Agricultural Science
• /
• v.45 no.1
• /
• pp.128-136
• /
• 2018

The Anti-corruption Law has been enforced since Sep. 28, 2016 to prevent public servants from colluding with people for political favors and financial gain by giving bribes to public servants. Generally, most people in Korea think that the law has had a positive effect on society. Under this law, people believe that our society has become more transparent. However, domestic producers think the law has had negative effects on the Korean livestock industry. Statistics from the domestic livestock industry show that the Hanwoo price has dropped after the law was enforced. This study attempts to show how livestock prices in the Korean livestock industry have changed after the enactment of the law. We chose three important livestock industries, Hanwoo, pork, and chicken, to determine and compare the effects of the law on them. For the analysis, we used a time-series model, VAR, to incorporate the interactions of the three industries. We selected the average wholesale prices of these industries. Daily prices during the last 5 years were used to estimate and forecast the impacts of the law. The results show that the price of Hanwoo decreased after the enforcement of the law; however, the other livestock prices did not decrease. Additionally, we clearly saw this negative effect on the Hanwoo industry during the high demand season and New Year's Day (solar and lunar together).

• Environmental and Resource Economics Review
• /
• v.15 no.5
• /
• pp.799-826
• /
• 2006

Combining recent advances in causal flows with time series analysis, relationships among eight North American natural gas spot market prices are examined. Results indicate that price discovery tends to occur in excess demand regions and move to excess supply regions. Across North America, the U.S. Midwest region represented by Chicago spot market is the most important market for price discovery. The Ellisburg-Leidy Hub in Pennsylvania is important in price discovery, especially for markets in the eastern two-thirds of the U.S. Malin Hub in Oregon is important for the western markets including the AECO Hub in Alberta, Canada.

• The Transactions of the Korean Institute of Electrical Engineers A
• /
• v.53 no.7
• /
• pp.405-413
• /
• 2004

Traditionally, electrical power systems had the vertically-integrated industry structures based on the economics of scale. However power systems have been recently reformed to increase the energy efficiency of the power system. According to these trends, Korean power industry has been partially restructured, and the competitive generation market was opened in 2001. In competitive electric markets, correct demand data are one of the most important issue to maintain the flexible electric markets as well as the reliable power systems. However, the measuring load data can have the uncertainty because of mechanical trouble, communication jamming, and other things. To obtain the reliable load data, an efficient evaluation technique to adust the missing load data is needed. This paper analyzes the load pattern of historical real data and then the turned ARIMA (Autoregressive Integrated Moving Average) model, PCHIP(Piecewise Cubic Interporation) and Branch & Bound method are applied to seek the missing parameters. The proposed method is tested under a variety of conditions and tested with historical measured data from the Korea Energy Management Corporation (KEMCO).

• The Journal of Asian Finance, Economics and Business
• /
• v.7 no.9
• /
• pp.219-228
• /
• 2020

The study investigates the impact of inflation rate on economic growth to find the best-fit model for economic growth in Vietnam. The study applied Vector Autoregressive (VAR), cointegration models, and unit root test for the time-series data from 1996 to 2018 to test the inflation impact on the economic growth in the short and long term. The study showed that the two variables are stationary at lag first difference I(1) with 1%, 5% and 10%; trace test indicates two cointegrating equations at the 0.05 level, the INF does not granger cause GDP, the optimal lag I(1) and the variables are closely related as R2 is 72%. It finds that the VAR model's results are the basis to perform economic growth; besides, the inflation rate is positively related to economic growth. The results support the monetary policy. This study identifies issues for Government to consider: have a comprehensive solution among macroeconomic policies, monetary policy, fiscal policy and other policies to control and maintain the inflation and stimulate growth; set a priority goal for sustainable economic growth; not pursue economic growth by maintaining the inflation rate in the long term, but take appropriate measures to stabilize the inflation at the best-fitted VAR forecast model.

• KIPS Transactions on Software and Data Engineering
• /
• v.6 no.12
• /
• pp.565-572
• /
• 2017

Traditional method for time series analysis, autoregressive integrated moving average (ARIMA) allows to mine significant patterns from the past observations using autocorrelation and to forecast future sequences. However, Korean baseball games do not have regular intervals to analyze relationship among the past attendance observations. To address this issue, we propose artificial neural network (ANN) based attendance prediction model using various measures including performance, team characteristics and social influences. We optimized ANNs using grid search to construct optimal model for regression problem. The evaluation shows that the optimal and ensemble model outperform the baseline model, linear regression model.

• Journal of Internet Computing and Services
• /
• v.11 no.4
• /
• pp.85-94
• /
• 2010

In this paper, we propose a location-prediction structure that can provide user service in advance. It consists of seven steps and supplies intelligent services which can forecast user's location. Context information collected from physical sensors and a history database is so difficult that it can't present importance of data and abstraction of data because of heterogeneous data type. Hence, we offer the location-prediction that change data type from heterogeneous data to homogeneous data. Extracted data is clustered by SOFM, then it gets user's location information by ARIMA and realizes the services by a reasoning engine. In order to validate the proposed location-prediction, we built a test-bed and test it by the scenario.

• Journal of the Korean Society of Fisheries and Ocean Technology
• /
• v.32 no.3
• /
• pp.235-240
• /
• 1996

Forecasts of monthly landings of walleye pollock, Theragra chalcogramma, in Korea were carried out by the seasonal Autoregressive Integrated Moving Average(ARlMA) model. The Box - Cox transformation on the walleye pollock catch data handles nonstationary variance. The equation of Box - Cox transformation was Y'=($Y^0.31$_ 1)/0.31. The model identification was determined by minimum AIC(Akaike Information Criteria). And the seasonal ARlMA model is presented (1- O.583B)(1- $B^1$)(l- $B^12$)$Z_t$ =(l- O.912B)(1- O.732$B^12$)et where: $Z_t$=value at month t ; $B^p$ is a backward shift operator, that is, $B^p$$Z_t$=$Z_t$-P; and et= error term at month t, which is to forecast 24 months ahead the walleye pollock landings in Korea. Monthly forecasts of the walleye pollock landings for 1993~ 1994, which were compared with the actual landings, had an absolute percentage error(APE) range of 20.2-226.1 %. Thtal observed annual landings in 1993 and 1994 were 16, 61OM/T and 1O, 748M/T respectively, while the model predicted 10, 7 48M/T and 8, 203M/T(APE 37.0% and 23.7%, respectively).

• Environmental and Resource Economics Review
• /
• v.10 no.2
• /
• pp.217-234
• /
• 2001

The use of district heating is expanding very rapidly in Korea. High population densities and the relatively cold winters make district heating an economically attractive option. About 8 percent of Korean houses are already using district heating and the government is seeking to aggressively expand this number. It has set a target of 15 percent of the residential heat market to be met by district heating in the year 2001. The main purpose of this paper is to analyze the consumption behavior of households using district heating. By pooling time-series and cross-sectional data for 12 apartment complexes in Seoul area, a single demand function is estimated and used to forecast the amounts of heat demanded by the individual households. The results shows that the level of consumption varies among households, depending on the non-economic factors such as the installation of individual metering equipment and the volume of apartment building. When individual metering equipment is installed, the level of annual heat consumption per household declines, on average, about 22.1 Mcal per square meters, which is equivalent to 834 won per square meter in terms of heating expenditures. In case that the apartment building was built in more than 6 stories, annual consumption level reduces additionally about 17.3 Mcal per square meters and, thus, save the expenditures by 649 Won per square meters, compared to the opposite case.

• Water for future
• /
• v.11 no.2
• /
• pp.54-61
• /
• 1978

An attemption of synthesizing and forecasting of monthly river flow has been made by employing a linear stochastic difference equation model. As one of the linear stochestic difference equation model, an ARIMA Type is tested to find the suitability of the model to the monthly river flows. On the assumption of the stationary covariacne of differenced monthly river flows the model is identrfield and is evaluated so that the residuale have the minimum variance. Finally a test is performed to finld the residerals beings White noise. Monthly river flows at six stations in Han River Basin are applied for case studies. It was found that the difference operator is a good measure of forecasting the monthly river flow.