• Proceedings of the KSR Conference
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• 2011.05a
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• pp.1572-1581
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• 2011

Since 'The Act on Private Investment of The Infrastructure' was established in 1994, private investment as well as government's investment has been active on transport infrastructure. But investment of transport infrastructure has more risks than others due to overforecast of transport demand for ensuring project validity, and cost uncertainty arising from financial crisis, commodity prices and so on. In the case of Incheon international airport express, after 2 years and 6 months, Incheon international airport express is opened, Korail take over equity stake in private investor due to the problems of MRG(Minimum Revenue Guarantee) be contracted with private investor. Not only that, in other case of Yong-in light rail, it is ongoing for legal disputes between Yong-in local government and private investor on account of opening delaying. On current Investment Assessment System of Transport Infrastructure, Risk Management system on investment of transport infrastructure is inadequate because Sensitivity Analysis in economic efficiency have been performed on the simple method which only changes benefits, expense and social discount rate. For this reason, this study analyze risks for investment of transport infrastructure demand forecast, and rise to the management practice for every particular item.

• Journal of Korean Society of Water and Wastewater
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• v.11 no.1
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• pp.109-118
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• 1997

In this study, we examined the structural analysis of water demand fluctuation for water distribution control of water supply network. In order to analyze for the length of stationary time series, we calculate autocorrelation coefficient of each case equally divided data size. As a result, it was found that, with the data size of around three months, any case could be used as stationary time series. we analyze cross-correlation coefficient between the daily water consumption's data and primary influence factors. As a result, we have decided to use weather conditions and maximum temperature as natural primary factors and holidays as a social factor. Applying the multiple ARIMA model, we obtains an effective model to describe the daily water demand prediction. From the forecasting result, even though we forecast water distribution quantity of the following year, estimated values well express the flctuations of measurements. Thus, the suitability of the model for practical use can be confirmed. When this model is used for practical water distribution control, water distribution quantity for the following day should be found by inputting maximum temperature and weather conditions obtained from weather forecast, and water purification plants and service reservoirs should be operated based on this information while operation of pumps and valves should be set up. Consequently, we will be able to devise a rational water management system.

• Journal of Information Technology Applications and Management
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• v.22 no.2
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• pp.201-217
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• 2015

In this paper, we report computational testing result to examine the validity of firm's bankruptcy risk estimation through quantification of supply chain risk. Supply chain risk in this study refers to upstream supply risk and downstream demand risk, To assess the firm's risk affected by supply chain risk, we adopt unit of analysis as industry level. since supply and demand relationships of the firm could be generalized by the industry input-output table and the availability of various valid economic indicators which are chronologically calculated. The research model to estimate firm's risk level is the linear regression model to assess the industry bankruptcy risk estimation of the focal firm's industry with the independent variables which could quantitatively reflect demand and supply risk of the industry. The publicly announced macro economic indicators are selected as the candidate independent variables and validated through empirical testing. To validate our approach, in this paper, we confined our research scope to steel industry sector and its related industry sectors, and implemented the research model. The empirical testing results provide useful insights to further refine the research model as the valid forecasting mechanism to capture firm's future risk estimation more accurately by adopting supply chain industry risk aspect, in conjunction with firm's financial and other managerial factors.

• Journal of Korean Society of Transportation
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• v.21 no.6
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• pp.43-55
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• 2003

This paper presents a new method for estimating potential transit ridership residential population and number of employees that have accesses to transit services. A standard procedure that can be used to determine transit accessibility by pedestrians ad automobiles are developed to improve its transit demand forecasting capability. The analysis results are compared with those from the traditional buffer method as well as the network ratio method. It was found that the proposed method is more accurate than the traditional methods. The new method can be used to better estimate the "Walk Access" transit trips and "Auto Access" transit trips in the Mode Choice Model.

• The Proceedings of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.6 no.3
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• pp.43-49
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• 1992

Forecasting of electric power demand has been a basic element for electric power system operation and system development, and it's accuracy has very strong influence on reliability and economical efficience of power supply. So, in this paper, long―term maximum electric power demand has been forecasted by using the triple exponential smoothing method initiated R.G.Brown. It has been regarded this method as high accuracy and operational convenience. The smoothing function is a liner combination of all past observations and the weight given to previous observations decreases geometrically with age.

• Journal of Korean Society of Water and Wastewater
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• v.23 no.2
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• pp.251-255
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• 2009

Foreign and domestic seawater desalination plant market investigation was performed to analyze the worldwide trend of seawater desalination plant market and to establish the activation plan for seawater desalination plant application. Water demand and seawater desalination related laws and regulations were investigated and analyzed for the activation plan. RO type and large scale plants are popular nowadays however there are only small plants in island region in Korea. There will be about $1 million\;m^3/day$ deficit in 2015 according to the water demand forecasting from Ministry of Environment and Ministry of Land, Transportation, and Maritime Affairs in Korea. Therefore, it is necessary to activate the domestic application of seawater desalination plant to secure stable water resources. To activate the domestic application of seawater desalination plant, first, we need to establish regulations, support system in the water service law for seawater desalination plant. Second, related Ministry should increase the support for the operation and management of seawater desalination plant and suggest the construction of seawater desalination plant for water resources security near seaside region.

• International Journal of Computer Science & Network Security
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• v.24 no.4
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• pp.147-154
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• 2024

The continuous increase in urban population due to migration of mases from rural areas to big cities has set urban water supply under serious stress. Urban water resources face scarcity of available water quantity, which ultimately effects the water supply. It is high time to address this challenging problem by taking appropriate measures for the improvement of water utility services linked with better understanding of demand side management (DSM), which leads to an effective state of water supply governance. We propose a dynamic framework for preventive DSM that results in optimization of water resource management. This paper uses Agent Based Modeling (ABM) with Digital Twin (DT) to model water consumption behavior of a population and consequently forecast water demand. DT creates a digital clone of the system using physical model, sensors, and data analytics to integrate multi-physical quantities. By doing so, the proposed model replicates the physical settings to perform the remote monitoring and controlling jobs on the digital format, whilst offering support in decision making to the relevant authorities.

• Journal of Korean Society of Forest Science
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• v.65 no.1
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• pp.80-91
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• 1984

The purposes of this study are to analyze and forecast the domestic demand for papers by regression models with time-series data (1965-81). For the period of 1965-81, the real GNP of Korea grew at annual average increase rate of 8.8 percent. On the other hand, the domestic demand of papers grew at annual average increase rate of 17.9 percent in this period. Especially, the annual average increase rate for board-papers accounted to 25.8 percent. To analyze domestic demand for papers, GNP, per capita GNP, price findex of papers, production activity index of the major papers consuming industries and price index of substitutive goods were selected as independent variables. The expected values of domestic demand for papers were computed by forecasting equations as follows. T-values are in parentheses. ${\ell}nDDP=2.452+1.986{\ell}nPG-0.844{\ell}nPWI$ $(33.397)^*\;(-6.149)^*\;R^2=0.997$ ${\ell}nDDP=6.468+0.827{\ell}nPDA$ $(17.403)^*\;R^2=0.950$ DDP : Domestic demand for papers PG : Real GNP per capita (1,000 won) PWI : Real price index of papers (1980 = 100) PDAV : Production activity index of the major papers consuming industries The results analyzed and forecasted by these models are summarized as follows: The domestic demand for papers had positive correlation toward per capita GNP and production activity index of the major papers consuming industries. Per capita GNP elasticity of the domestic demand for papers was the most elastic among independent variables. The price elasticity of domestic demand for papers had negative sign and inelastic. These were not only statistically significant but theoretically compatible. The domestic demand for papers was projected to be 3,152-4,470 thousand mit in 1991, representing at annual increase rate of 5.0-12.4 percent during the period of 1982-91. Domestic demand for papers per capita was projected to be 69.1-98.0 kg in 1991.

• Journal of Information Technology Services
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• v.19 no.4
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• pp.49-61
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• 2020

Prior studies on technology predictions attempted to predict the emergence and spread of emerging technologies through the analysis of correlations and changes between data using objective data such as patents and research papers. Most of the previous studies predicted future technologies only from the viewpoint of technology development. Therefore, this study intends to conduct technical forecasting from the perspective of the consumer by using keyword search frequency of search portals such as NAVER before and after the introduction of emerging technologies. In this study, we analyzed healthcare technologies into three types : measurement technology, platform technology, and remote service technology. And for the keyword analysis on the healthcare, we converted the classification of technology perspective into the keyword classification of consumer perspective. (Blood pressure and blood sugar, healthcare diagnosis, appointment and prescription, and remote diagnosis and prescription) Naver Trend is used to analyze keyword trends from a consumer perspective. We also used the ARIMA model as a technology prediction model. Analyzing the search frequency (Naver trend) over 44 months, the final ARIMA models that can predict three types of healthcare technology keyword trends were estimated as "ARIMA (1,2,1) (1,0,0)", "ARIMA (0,1,0) (1,0,0)", "ARIMA (1,1,0) (0,0,0)". In addition, it was confirmed that the values predicted by the time series prediction model and the actual values for 44 months were moving in almost similar patterns in all intervals. Therefore, we can confirm that this time series prediction model for healthcare technology is very suitable.