• Journal of Korean Society of Transportation
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• v.22 no.2 s.73
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• pp.19-26
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• 2004

AllWayS(AWS, Satongpaldal in Korean) is the first comprehensive computer software in Korea that is developed for the transportation demand modeling. The original DOS version software was recently receded for Windows environment. Traditional 4-step transportation demand forecasting process is incorporated in the software under graphical user interface environment. AWS is able to compose or edit graphic transportation networks data by each scenario which could be the subject of an analysis. Besides, it use database structure that can handle every data of a scenario such as networks, O/D, and socio-economic data, etc. We expect this integrated process could provide each analyst with efficient and easy to use tool for their analysis. Each models in this software is based on traditional algorithms and the results were compared to existing software, EMME/2 and it showed similar results.

• Journal of Technology Innovation
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• v.23 no.2
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• pp.33-54
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• 2015

Supercomputing performance demand forecasting at the national level is an important information to the researchers in fields of the computational science field, the specialized agencies which establish and operate R&D infrastructure, and the government agencies which establish science and technology infrastructure. This study derived the factors affecting the scientific and technological capability through the analysis of supercomputing performance prediction research, and it proposed a hybrid forecasting model of applying the super-computer technology trends. In the cross-sectional analysis, multiple regression analysis was performed using factors with GDP, GERD, the number of researchers, and the number of SCI papers that could affect the supercomputing performance. In addition, the supercomputing performance was predicted by multiplying in the cross-section analysis with technical progress rate of time period which was calculated by time series analysis using performance(Rmax) of Top500 data. Korea's performance scale of supercomputing in 2016 was predicted using the proposed forecasting model based on data of the top500 supercomputer and supercomputing performance demand in Korea was predicted using a cross-sectional analysis and technical progress rate. The results of this study showed that the supercomputing performance is expected to require 15~30PF when it uses the current trend, and is expected to require 20~40PF when it uses the trend of the targeting national-level. These two results showed significant differences between the forecasting value(9.6PF) of regression analysis and the forecasting value(2.5PF) of cross-sectional analysis.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.12
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• pp.8576-8584
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• 2015

Load forecasting is needed to make supply and demand plan for a stable supply of electricity. It is also necessary for optimal operational plan of the power system planning. In particular, in order to ensure stable power supply, long-term load forecasting is important. And regional load forecasting is important for tightening supply stability. Regional load forecasting is known to be an essential process for the optimal state composition and maintenance of the electric power system network including transmission lines and substations to meet the load required for the area. Therefore, in this paper we propose a forecasting method using SARIMA during the 12 months (long-term/mid-term) load forecasting by 16 regions of the South Korea.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.5
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• pp.169-178
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• 2021

Recently, a bike-sharing system (BSS) has become popular as a convenient "last mile" transportation. Rebalancing of bikes is a critical issue to manage BSS because the rents and returns of bikes are not balanced by stations and periods. For efficient and effective rebalancing, accurate traffic prediction is important. Recently, cluster-based traffic prediction has been utilized to enhance the accuracy of prediction at the station-level and the clustering step is very important in this approach. In this paper, we propose a k-means based clustering algorithm that overcomes the drawbacks of the existing clustering methods for BSS; indeterministic and hardly converged. By employing the centroid initialization and using the temporal proportion of the rents and returns of stations as an input for clustering, the proposed algorithm can be deterministic and fast.

• The Journal of the Convergence on Culture Technology
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• v.8 no.6
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• pp.861-866
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• 2022

Seoul introduced the shared bicycle system, "Seoul Public Bike" in 2015 to help reduce traffic volume and air pollution. Hence, to solve various problems according to the supply and demand of the shared bicycle system, "Seoul Public Bike," several studies are being conducted. Most of the research is a strategic "Bicycle Rearrangement" in regard to the imbalance between supply and demand. Moreover, most of these studies predict demand by grouping features such as weather or season. In previous studies, demand was predicted by time-series-analysis. However, recently, studies that predict demand using deep learning or machine learning are emerging. In this paper, we can show that demand prediction can be made a little better by discovering new features or ordering the importance of various features based on well-known feature-patterns. In this study, by ordering the selection of new features or the importance of the features, a better coefficient of determination can be obtained even if the well-known deep learning or machine learning or time-series-analysis is exploited as it is. Therefore, we could be a better one for demand prediction.

• Economic and Environmental Geology
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• v.23 no.4
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• pp.383-392
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• 1990

This study found that that dynamics of intensity of use and economic theory of derived demand can both be accommodated through an extensive translog demand model. The basic idea in this recognition is that the skewed life cycle empirical pattern of intensity of use plotted against per capita income is of lognormal form and this lognomal intensity of use model can be mathematically transformed into an eqivalent simple translog intensity of use model. Empirical results showed that this extensive traslog model, which is a flexible function and includes both the classical case of fixed coefficients and the dynamic case of varying coefficients of the explanatory variables, gave better forecasts than the original intensity of use model and other conventional models.

• 전기의세계
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• v.46 no.5
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• pp.11-18
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• 1997

다가오는 21세기는 삶의 질 향상과 산업의 선진국화 생활환경의 자동화 및 정보화로의 전이등으로 전력수요가 급격히 증가할 것이다. 장기 전력수요예측[1]에 의하면 1995년 29,878MW였던 최대부하가 2000년 43,500MW, 2005년 55,700MW, 2010년 65,600MW가 될 것으로 예측하고 있다. 이에 따라 커지는 전력유통을 원활하게 하기 위하여 한전에서는 기존 345kV 송전선로의 5배의 송전능력을 가진 765kV 송전선로를 건설하고 있다. 765kV 송전선로는 국내 최고의 전압으로서 최초로 건설될 뿐만 아니라 제 1단계로 건설에 착수한 물량도 340km를 일시에 시행하는 대규모이다. 이와같은 사업의 시작부터 지금까지 추진한 내용과 공사에 새롭게 적용하는 기술, 공법등에 대하여 기술하고자 한다.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.2
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• pp.93-95
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• 2006

최근 LNG 선박의 발주량이 급증함에 따라 LNG 선에 승무할 인력의 심각한 부족이 예상되고 있다. 이러한 LNG 선박에 승무할 인력 특히 고급 사관의 부족은 선박 자체의 안전뿐 아니라 궁극적으로는 LNG 수송체계의 안전에도 큰 영향을 미치게 될 것이다. 이 발표에서는 현재 전세계 상선대의 현황에서 출발하여, 최근 LNG 선박의 발주 현황, LNG 선박에 적용되는 최신 기술 및 엔진 등에 대하여 살펴 본 후에 전세계 LNG 선박 수주 잔량을 근거로 하여 필요 인력을 예측해 본다.

• Journal of the Korean Data and Information Science Society
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• v.6 no.1
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• pp.23-30
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• 1995

이동전화 서비스에 대한 가입자수는 중단기적으로 급격히 증가하지만 장기적으로는 대체서비스의 개발 등의 영향으로 그 증가율이 감소하는 특징을 가지고 있다. 본 연구에서는 이동전화 수요에 영향을 미치는 사회 경제 및 기술적 변수들에 대한 통계분석과 아울러 우리나라의 이동전화 가입자수를 예측하였다. 수요의 특성에 따라 로지스틱모형과 이동평균모형을 적용하여 예측한 결과 2001년에는 660만명에 달하여 이동전화의 대중화 시대가 본격적으로 전개될 전망이다.

• Journal of Korean Society of Transportation
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• v.27 no.2
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• pp.83-91
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• 2009

This paper aims to predict air passenger and air freight demands in the air routes between South and North Korea. The air demands will be fostered by the visitors of Pyeongyang and Baekdu Mountain, whose forecasts will be used for supplying the air traffic services necessary for the active exchange and cooperation between South and North Korea in the future. The authors use the tool of regression analysis under the assumption of epoch-making progress in demand for aviation in accordance with the exchange and cooperation scenario between South and North Korea. After predicting the total number of travelers through regression analysis, the authors applied the share of air passengers among total travelers in order to predict the number of air passengers. Finally, the number of flights of each airport and route were forecasted by including the air freight, estimated from the number of air passengers.