• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.11
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• pp.1503-1510
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• 2014

This study organizes scenarios on the power supply plans and electricity load forecasts considering their uncertainties and estimates natural gas quantity for electricity generation, total electricity supply cost and air pollutant emission of each scenario. Also the analysis is performed to check the properness of government's natural gas demand forecast and the possibility of achieving the government's CO2 emission target with the current plan and other scenarios. In result, no scenario satisfies the government's CO2 emission target and the natural gas demand could be doubled to the government's forecast. As under-forecast of natural gas demand has caused the increased natural gas procurement cost, it is required to consider uncertainties of power plant construction plan and electricity demand forecast in forecasting the natural gas demand. In addition, it is found that CO2 emission target could be achieved by enlarging natural gas use and demand-side management without big increase of total costs.

• Journal of Energy Engineering
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• v.18 no.2
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• pp.114-124
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• 2009

The Ministry of Knowledge and Economy (MKE) establishes the Basic Plan for Long-Term Electricity Supply and Demand(BPE) biannually, a governmental plan for the stable electricity supply. This study investigated the effects of the electric demand forecast on the energy mix. A simplified simulation model was developed, which replaces the WASP program developed by the KPX and verified by comparing both results. Three different electric demand scenarios were devised based upon the 2005 electric demand forecast: Proper, 5 % higher, and 5% lower. The simplified model calculates the energy mix for each scenario of the year 2005. Then it calculates the energy mix for the proper electric demand forecast of the year 2007 using the energy mixes of the three scenarios as the initial conditions, so that it reveals the effect of electric demand forecast of the previous BPE on the energy mix of the next BPE. As the proper electric demand forecasts of the year 2005 and 2007 are the same, there is no change in the previous and the next BPEs. However when the electric demand forecasts were 5% higher in the previous BPE and proper in the next BPE, some of the planned power plant construction in the previous BPE had to be canceled. Similarly, when the electric demand forecasts were 5% lower in the previous BPE and proper in the next BPE, power plant construction should be urgently increased to meet the increased electric demand. As expected the LNG power plants were affected as their construction periods are shorter than coal fired or nuclear power plants. This study concludes that the electric demand forecast is very important and that it has the risk of long term energy mix.

• Journal of Korea Port Economic Association
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• v.32 no.4
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• pp.1-13
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• 2016

This study attempts to establish a precise forecast model for the container inventory demand of shipping companies through forecasts based on equipment type/size, ports, and weekly system dynamics. The forecast subjects were Shanghai and Yantian Ports. Only dry containers (20, 40) and high cubes (40) were used as the subject container inventory in this study due to their large demand and valid data computation. The simulation period was from 2011 to 2017 and weekly data were used, applying the actual data frequency among shipping companies. The results of the model accuracy test obtained through an application of Mean Absolute Percentage Error (MAPE) verified that the forecast model for dry 40' demand, dry 40' high cube demand, dry 20' supply, dry 40' supply, and dry 40' high cube supply in Shanghai Port provided an accurate prediction, with $0%{\leq}MAPE{\leq}10%$. The forecast model for supply and demand in Shanghai Port was otherwise verified to have relatively high prediction power, with $10%{\leq}MAPE{\leq}20%$. The forecast model for dry 40' high cube demand and dry 20' supply in Yantian Port was accurate, with $0%{\leq}MAPE{\leq}10%$. The forecast model for supply and demand in Yantian Port was generally verified to have relatively high prediction power, with $10%{\leq}MAPE{\leq}20%$. The forecast model in this study also had relatively high accuracy when compared with the actueal data managed in shipping companies.

• Korean Journal of Childcare and Education
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• v.12 no.6
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• pp.123-137
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• 2016

The purpose of this study was to forecast demand of childcare teachers based ion four different scenarios. In order to, the demand for childcare teachers from 2015 to 2024 were forecasted using time series techniques with data on the number of childcare teachers from 2003 to 2014. Results were as followings. Firstly, the demand for childcare teachers was expected to increase until 2019, but after 2020 steadily decreased in terms of scenario 1(child teacher ratio regulation). According to scenario 2(child teacher ratio based on 17 cities and provinces), the demand for childcare teachers was expected to need 440 teachers more until 2016. Then, according to scenario 3(two teachers each class), Scenario 4-1(one teacher and one staff each 2 toddler class and 3 older class) and scenario 4-2(one teacher and one staff each class), the demand of childcare teachers and staffs were estimated. These results implicated that childcare teachers and staffs supply policy would be established according to forecast demand.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2018.05a
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• pp.332-333
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• 2018

The master plan for aggregate supply and demand aims to ensure the feasibility viability of mid/long-term aggregate supply and demand by establishing comprehensive plans for regional groups and aggregate types. In addition, It will propose ways to reduce the environmental impact of the development of aggregates and to stabilize aggregate supply and demand across the country. Also, it will seek to promote the stable development of the construction industry through policy and related amendments.

• Journal of Biosystems Engineering
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• v.38 no.1
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• pp.9-17
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• 2013

Purpose: The goal of this study was to develop a methodology for the demand forecast of tractor, riding type rice transplanter and combine harvester using an ARIMA (autoregressive integrated moving average) model, one of time series analysis methods, and to forecast their demands from 2012 to 2021 in South Korea. Methods: To forecast the demands of three kinds of machines, ARIMA models were constructed by following three stages; identification, estimation and diagnose. Time series used were supply and stock of each machine and the analysis tool was SAS 9.2 for Windows XP. Results: Six final models, supply based ones and stock based ones for each machine, were constructed from 32 tentative models identified by examining the ACF (autocorrelation function) plots and the PACF (partial autocorrelation function) plots. All demand series forecasted by the final models showed increasing trends and fluctuations with two-year period. Conclusions: Some forecast results of this study are not applicable immediately due to periodic fluctuation and large variation. However, it can be advanced by incorporating treatment of outliers or combining with another forecast methods.

• Journal of Korean Society of Water and Wastewater
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• v.20 no.2
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• pp.187-196
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• 2006

Forecasting the long-term water demand is important in the plan of water supply system because the location and capacity of water facilities are decided according to it. To forecast the long-term water demand, the existing method based on lpcd and population has been usually used. But, these days the trend among the variation of water demand has been disappeared, so expressing other variation of it is needed to forecast correct water demand. To accomplish it, we introduced the System Dynamics method to consider total connections of water demand factor. Firstly, the factors connected with water demand were divided into three sectors(water demand, industry, and population sectors), and the connections of factors were set with multiple regression model. And it was compared to existing method. The results are as followings. The correlation efficients are 0.330 in existing model and 0.960 in SD model and MAE are 3.96% in existing model and 1.68% in SD model. So, it is proved that SD model is superior to the existing model. To forecast the long-term water demand, scenarios were made with variations of employment condition, economic condition and consumer price indexes and forecasted water demands in 2012. After all scenarios were performed, the results showed that it was not needed to increase the water supply ability in Seoul.

• Korean Journal of Construction Engineering and Management
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• v.10 no.2
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• pp.46-54
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• 2009

In the early 90s, we had serious shortage of construction engineers for the expansion of construction market. So, Government has established the admitted engineer system in 1995. However, since year 2000, while the engineershortage has been resolved, the opposite situation has occurred: serious over-supply of construction engineers. Therefore, Government announced that would abolish the admitted engineer systems as recognized the existent admitted engineers from 2007. From this point of view, it is critical to make the accurate forecast of number of required construction engineers for providing the basis for the most appropriate policy from 2008 to 2017. This research have developed a construction engineer supply-demand forecast model based on the GDP and construction market analysis. The results of this research will be applied to the basic data that policy planner establishes the supply-demand policy of construction engineers.

• Korean Journal of Agricultural Science
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• v.49 no.3
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• pp.679-690
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• 2022

As the supply and demand of pork has become a significant concern in Korea, controlling it has become a critical challenge for the industry. However, compared to the demand for pork, which has relatively stable consumption, it is not easy to maintain a stable supply. As the preparation of measures for a supply-demand crisis response and supply control in the pig industry has emerged as an important task, it has become necessary to establish a stable supply model and create an appropriate manual. In this study, a pork supply prediction model is constructed using reported data from the pig traceability system. Based on the derived results, a method for determining the supply-demand crisis stage using a statistical approach was proposed. From the results of the analysis, working days, African swine fever, heat wave, and Covid-19 were shown to affect the number of pigs graded in the market. A test of the performance of the model showed that both in-sample error rate and out-sample error rate were between 0.3 - 7.6%, indicating a high level of predictive power. Applying the forecast, the distribution of the confidence interval of the predicted value was established, and the supply crisis stage was identified, evaluating supply-demand conditions.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2006.11a
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• pp.453-457
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• 2006

After the introduction of Professional Engineer System to secure superior technical personnel in 1963, the engineering license regulations were introduced in 1995 - the person qualified with either the academic back ground or career in the construction field can be authorized as a construction engineer- to cope with higher demands for construction engineers caused by revitalization of construction business such as 2 million house construction. As a result, the number of construction engineers has been increased drastically since year 2000, which caused serious problems in utilizing top technical certificate, the PE's. Recently, relating to the opening of technology market according to WTO agreement and mutual authentication among countries and etc., the government is preparing legal and systematic foundations to guarantee the professionalism of engineers. Through the exact supply-demand forecast of PE's reflecting these systematic aspects, we are going to analyze the problems in the supply-demand of PE's and suggest the systematic improvement plans for managing the supply-demand of PE's. The result of this research can be used for building efficient and consistent raising and utilizing system of PE's as well as supply and demand system of qualified PE's