• Journal of Korea Port Economic Association
• /
• v.23 no.1
• /
• pp.149-162
• /
• 2007

The purpose of this study is to forecast the marine trading volumes using multiplicative seasonal Autoregressive Integrated Moving Average(ARIMA) model. The paper proceeds by comparing the forecasting performances of the unload volumes with those of the load volumes with Box-Jenkins ARIMA model. Also, I present the predicted values based on the ARIMA model. The result shows that the trading volumes increase very slowly.

• Geomechanics and Engineering
• /
• v.36 no.5
• /
• pp.465-474
• /
• 2024

Uniaxial compressive strength (UCS) is a critical geomechanical parameter that plays a significant role in the evaluation of rocks. The practice of indirectly estimating said characteristics is widespread due to the challenges associated with obtaining high-quality core samples. The primary aim of this study is to investigate the feasibility of utilizing the gene expression programming (GEP) technique for the purpose of forecasting the UCS for various rock categories, including Schist, Granite, Claystone, Travertine, Sandstone, Slate, Limestone, Marl, and Dolomite, which were sourced from a wide range of quarry sites. The present study utilized a total of 170 datasets, comprising Schmidt hammer (SH), porosity (n), point load index (Is(50)), and P-wave velocity (Vp), as the effective parameters in the model to determine their impact on the UCS. The UCS parameter was computed through the utilization of the GEP model, resulting in the generation of an equation. Subsequently, the efficacy of the GEP model and the resultant equation were assessed using various statistical evaluation metrics to determine their predictive capabilities. The outcomes indicate the prospective capacity of the GEP model and the resultant equation in forecasting the unconfined compressive strength (UCS). The significance of this study lies in its ability to enable geotechnical engineers to make estimations of the UCS of rocks, without the requirement of conducting expensive and time-consuming experimental tests. In particular, a user-friendly program was developed based on the GEP model to enable rapid and very accurate calculation of rock's UCS, doing away with the necessity for costly and time-consuming laboratory experiments.

• The Transactions of the Korea Information Processing Society
• /
• v.4 no.7
• /
• pp.1749-1758
• /
• 1997

This paper suggests the development of dynamic forecasting model for short-term power demand based on Radial Basis Function Network and Pal's GLVQ algorithm. Radial Basis Function methods are often compared with the backpropagation training, feed-forward network, which is the most widely used neural network paradigm. The Radial Basis Function Network is a single hidden layer feed-forward neural network. Each node of the hidden layer has a parameter vector called center. This center is determined by clustering algorithm. Theatments of classical approached to clustering methods include theories by Hartigan(K-means algorithm), Kohonen(Self Organized Feature Maps %3A SOFM and Learning Vector Quantization %3A LVQ model), Carpenter and Grossberg(ART-2 model). In this model, the first approach organizes the load pattern into two clusters by Pal's GLVQ clustering algorithm. The reason of using GLVQ algorithm in this model is that GLVQ algorithm can classify the patterns better than other algorithms. And the second approach forecasts hourly load patterns by radial basis function network which has been constructed two hidden nodes. These nodes are determined from the cluster centers of the GLVQ in first step. This model was applied to forecast the hourly loads on Mar. $4^{th},\;Jun.\;4^{th},\;Jul.\;4^{th},\;Sep.\;4^{th},\;Nov.\;4^{th},$ 1995, after having trained the data for the days from Mar. $1^{th}\;to\;3^{th},\;from\;Jun.\;1^{th}\;to\;3^{th},\;from\;Jul.\;1^{th}\;to\;3^{th},\;from\;Sep.\;1^{th}\;to\;3^{th},\;and\;from\;Nov.\;1^{th}\;to\;3^{th},$ 1995, respectively. In the experiments, the average absolute errors of one-hour ahead forecasts on utility actual data are shown to be 1.3795%.

• Journal of Korean Society on Water Environment
• /
• v.35 no.3
• /
• pp.209-223
• /
• 2019

Broadly speaking, in order to analyze the water quality improvement effects of the implementation of the Total Water Pollutant Management System in the Sapgy-Lake waterways, a reference was made to the [Plans for implementation of the Total Maximum Daily Load(TMDL)] in 3 cities (Cheonan, Asan, Dangjin). The results of the investigation into the plans to reduce the pollutant load show in that region show that there are plans to reduce pollution for a total of 16 reduction facilities. As for the result of the computation of the reduction in the load, these measurements were computed at the Gokgyo-stream basin and Namwon-stream basin, with BOD and T-P at the Gokgyo-stream basin reduced by 13.9 % and 13.3 %, respectively, while BOD and T-P at the Namwon-stream were reduced by 3.7 % and 3.3 %, respectively. In this way, thus using the results of the water quality forecast of Sapgyo-Lake in measures for the improvement of water quality (in accordance with the implementation of the TMDL), and using the QUAL-MEV model and EFDC model, it is noted that BOD will be improved by 26.4 % from 6.1 mg/L to 4.5 mg/L 0.0 %, T-P by 36.7 % from 0.168 mg/L to 0.107 mg/L and TOC by 26.4 % from 7.7 mg/L to 5.6 mg/L. However, it is forecasted that the targeted standards for the medium influence area will not be achieved. Evidently, Gokgyo-stream and Namwon-stream have been implementing the Total Water Pollutant Management System for the BOD items since January 1, 2019, but the Sapgyo-stream and Muhan-stream were excluded from being designated as subject regions. As such, it is noted now that it is necessary to implement the TMDL for the entire Sapgyo-Lake water systems including Sapgyo-stream and Muhan-stream in order to improve the water quality of Sapgyo-Lake, and likewise the T-P should be designated as the substance subjected to management in addition to BOD.

• Journal of Environmental Science International
• /
• v.19 no.1
• /
• pp.39-45
• /
• 2010

When the Juam multipurpose dam which is connected with existing large water supply facilities is finished, water environment is changed from stream to lake. The changed quality of water should be examined. In this study, the result of water quality forecasting is analysed and an effective management plan of water quality is presented. Tn this study, the WASPS model that is a dynamic water quality simulation model was selected to forecast the water quality. This model forecasts movement of change of pollutants. For an application of the model, the subject areas were divided into seventeen sub-areas by considering change temperature depending measuring points and on depth of water. Meteorological data collected by the meteorological observatory and data about quality measured by the Korea Water Resources Development Corporation were used for an operation of the model. As a result of quality examination through quality data and estimated pollutant loading, the water quality environment criterion was grade II and the nutritive condition was measured as meso-graphic grade. In this study, an effective management was planned to improve water quality by reducing pollution load. According to the result of examination, when more than 30% of BOD was reduced it was recorded that the environment standard of water quality was improved to the second grade.

• Journal of Energy Engineering
• /
• v.11 no.1
• /
• pp.59-66
• /
• 2002

The vertically integrated power industry was divided into six generation companies and one market operator, where electricity trading was launched at power exchange. In this environment, the profits of each generation companies are guaranteed according to utilizing strategies of their own generation equipments. This paper presents on generator maintenance scheduling and efficient bidding strategies for generation equipments through the calculation of the contract and the application of each generator cost function based on the past demand forecasting error and market operating data.

• Proceedings of the KIEE Conference
• /
• 2011.07a
• /
• pp.364-365
• /
• 2011

This study develops a new system for generation system simulation and operational planning (namely, KPWR-X) including GMS(Generator Maintenance Scheduling), UC(Unit Commitment), and LF(Load Forecasting) for new power system environment in recent. The KPWR-X provides operator and planner to help the generation system more safely and economically. GUI developed in this study makes operator feel in convenient to control whole power system. In future, it is expected that generation company, ISO, and fuel procurement, etc. may use an instructional tool developer's suggestion for application. It will be also applicable to establish the operational strategies for generation control, fuel procurement and power system risk management.

• Environmental and Resource Economics Review
• /
• v.16 no.4
• /
• pp.901-922
• /
• 2007

To see how the electricity demand for air-conditioning responds to weather condition and what kind of weather condition works better in forecasting maximum daily electricity demand, four different regression models, which are linear, exponential, power and S-curve, are adopted. The regression outcome turns out that the electricity demand for air-conditioning is inclined to rely on the exponential model. Another major discovery of this study is that the electricity demand for air-conditioning responds more sensitively to the weather condition year after year along with the higher non-air-conditioning electricity demand. In addition, it has also been found that the discomfort index explains the electricity demand for air-conditioning better than the highest temperature.

• KIEAE Journal
• /
• v.9 no.4
• /
• pp.29-36
• /
• 2009

Artificial ground greening has been developed gradually in accordance with increasing demands of out-door space in Apartment complexes. Nowadays other social demand, environmental load abatement, needs qualitative growth of artificial ground greening as well as quantitative growth. So the objects of this study would be seizing and analyzing changeable items in artificial ground greening in the future, and show drafting materials for the development of spheres in connected with artificial ground greening. For this study, Delphi method was applied. First, three groups of panel, 48 people, were selected. Second, set up items of changes possible in the future from the first questionnaire and additional inquiry. Third, made up the second questionnaire of change possible in the future with Likert summated scale, and finally one way - ANOVA executed; independent variables were items of changes, and dependent variables were three groups of panel. To conclude, although limits of this study, we could glance over general flows and changes in artificial ground greening, and discover items which are hardly changeable and necessary to change in present condition of artificial ground greening.

• Proceedings of the KIEE Conference
• /
• 2005.11b
• /
• pp.142-144
• /
• 2005

본 연에서는 현재 전력거래소에서 사용하고 있는 단기수요예측 산법을 전력시장 운영환경에 대응 하도록 보다 정확하면서도 공정성이 보장되는 산법으로 개선하였다. 접근방법은 기존의 산법들을 면밀히 분석한 다음 산법의 개선과 매개변수의 튜닝을 통하여 예측정확도를 개선하였으며, 예측과정의 투명성을 확보하기 위하여 예측절차를 출력하는 기능을 포함하였다 예측정확도를 개선하기 위한 주요 방안으로 종합분석모형의 경우는 실적자료가 생길 때 마다 즉시 민감도가 갱신되도록 하였으며, 회귀분석모형은 분석과정에서 의미가 있는 자료만을 선택하도록 하였다. 또한 신경망 모형의 경우는 모의를 통하여 최적의 입력변수를 찾아 설정하였으며, 지식기반모형에서는 최근의 수요특성을 분석하여 새로운 규칙들로 구축하였다. 제안한 산법의 효용성을 평가하기 위하여 2004년도 실계통 자료를 대상으로 모의를 해 본 결과, 모든 산법에서 개선된 예측정확도를 나타내었다.