• 한국항해항만학회지
• /
• 제48권1호
• /
• pp.7-16
• /
• 2024

외항 상선 선박 척수가 증가하고 있지만, 한국인 해기사가 감소하여 인력 부족 문제가 심각하게 대두되고 있는 상황에서 본 연구는 외항 상선 해기사 인력 수요와 공급을 결정하는 요인들을 객관적으로 측정하여 정확한 인력 수요와 공급을 예측하고자 하였다. 인력 수요는 선박 규모별 필요 해기사 수의 차이를 반영하여 선박 증가 예측치에 이를 적용하여 직급별로 예측하였다. 인력 공급은 Markov모형을 활용하여 연도별 승진, 이직, 퇴직, 신규 진입 등의 증감요인을 반영하여 직급별 연령별로 세분화하여 예측하였다. 외항 상선 해기사 인력 수요는 2023년 11,638명에서 2030년 13,879명으로 증가하고, 공급은 2023년 7,006명에서 2030년 6,426명으로 감소하여 2040년에는 부족인원이 1만명을 넘는 것으로 예측되었다. 본 연구는 객관적인 데이터와 과학적 분석방법 및 논리적 추론을 통해 예측의 정확도를 제고하여 외항 상선해기사 인력 부족 문제를 해결하는데 유용한 자료로 활용될 수 있을 것이다.

• 농업과학연구
• /
• 제49권3호
• /
• pp.679-690
• /
• 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.

• Nuclear Engineering and Technology
• /
• 제52권6호
• /
• pp.1334-1339
• /
• 2020

This paper presents an empirical and comprehensive forecasting analysis of the uranium price. Prices are generally difficult to forecast, and the uranium price is not an exception because it is affected by many external factors, apart from imbalances between demand and supply. Therefore, a systematic analysis of multiple forecasting methods and combinations of them along repeated forecast origins is a way of discerning which method is most suitable. Results suggest that i) some sophisticated methods do not improve upon the Naïve's (horizontal) forecast and ii) Unobserved Components methods are the most powerful, although the gain in accuracy is not big. These two facts together imply that uranium prices are undoubtedly subject to many uncertainties.

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 2001년도 합동 추계학술대회 논문집 정보 및 제어부문
• /
• pp.61-64
• /
• 2001

The electric power load during the peak time in summer is strongly affected by cooling load. which decreases the preparation ratio of electricity and brings about the failure in the supply of electricity in the electric power system. The ice-storage system and heat pump system etc are used to settle this problem. In this study, the method of estimating temperature and humidity to forecast the cooling load of ice-storage system is suggested. And also the method of forecasting the cooling load using neural network is suggested. For the simulation, the cooling load is calculated using actual temperature and humidity. The forecast of the temperature, humidity and cooling load are simulated. As a result of the simulation, the forecasted data approached to the actual data.

• International Journal of Air-Conditioning and Refrigeration
• /
• 제11권4호
• /
• pp.170-177
• /
• 2003

The electric power load during the summer peak time is strongly affected by cooling load, which decreases the preparation ratio of electricity and brings about the failure in the supply of electricity in the electric power system. The ice storage system and heat pump system etc. are used to settle this problem. In this study, the method of estimating temperature and humidity to forecast the cooling load of ice storage system is suggested. The method of forecasting the cooling load using neural network is also suggested. The daily cooling load is mainly dependent on actual temperature and humidity of the day. The simulation is started with forecasting the temperature and humidity of the following day from the past data. The cooling load is then simulated by using the forecasted temperature and humidity data obtained from the simulation. It was observed that the forecasted data were closely approached to the actual data.

• 한국식생활문화학회지
• /
• 제5권4호
• /
• pp.481-485
• /
• 1990

This study is designed to forecast the characteristics in food consumption patterns under per capita GNP growth. Ordinary least square(OLS)method was employed as analyzing technique. Equation was $Y=a_0+a_1X$, in which X was per capita GNP and Y were Engel coefficient, food supply, energy supply, nutrient intake and ratio of self-supply of food. The result obtained indicates that the intake of nutrient such as protein and fat will be increased, and wheat, corn and legume are expected to be imported wholly due to lower ratio of self-supply, and rice will be over-supplied continually. Therefore, the relevant policy of government must be established in the field of supply and demand of food, and the research of sound national health should be done.

• 한국시스템다이내믹스연구
• /
• 제9권1호
• /
• pp.125-141
• /
• 2008

It is very difficult to predict future demand/supply, price for resources with acceptable accuracy using regression analysis. We try to use system dynamics to forecast the demand/supply and price for nickel. Nickel is very expensive mineral resource used for stainless production or other industrial production like battery, alloy making. Recent nickel price trend showed non-linear pattern and we anticipated the system dynamic method will catch this non-linear pattern better than the regression analysis. Our model has been calibrated for the past 6 year quarterly data (2002-2007) and tested for next 5 year quarterly data(2008-2012). The results were acceptable and showed higher accuracy than the results obtained from the regression analysis. And we ran the simulations for scenarios made by possible future changes in demand or supply related variables. This simulations implied some meaningful price change patterns.

• 상하수도학회지
• /
• 제14권3호
• /
• pp.281-290
• /
• 2000

This study investigates the prediction of daily water supply, which is a necessary for the efficient management of water distribution system. ANFIS, namely artificial intelligence, is a neural network into which fuzzy information is inputted and then processed. In this study, daily water supply was predicted through an application of network-based fuzzy inference system(ANFIS) for daily water supply prediction. This study was investigated methods for predicting water supply based on data about the amount of water which supplied in Kwangju city. For variables choice, four analyses of input data were conducted: correlation analysis, autocorrelation analysis, partial autocorrelation analysis, and cross-correlation analysis. Input variables were (a) the amount of water supply, (b) the mean temperature, and (c) the population of the area supplied with water. Variables were combined in an integrated model. Data of the amount of daily water supply only was modelled and its validity was verified in the case that the meteorological office of weather forecast is not always reliable. Proposed models include accidental cases such as a suspension of water supply. The maximum error rate between the estimation of the model and the actual measurement was 18.46% and the average error was lower than 2.36%. The model is expected to be a real-time estimation of the operational control of water works and water/drain pipes.

• 대한산업공학회지
• /
• 제35권3호
• /
• pp.203-212
• /
• 2009

The bullwhip effect refers to the phenomenon where demand variability is amplified when one moves upward a supply chain. In this paper, we exactly quantify the bullwhip effect for cases of seasonal demand processes in a two-echelon supply chain with a single retailer and a single supplier. In most of the previous research, some measures of performance for the bullwhip effect are developed for cases of non-seasonal demand processes. The retailer performs demand forecast with a multiplicative seasonal mixed model by using the minimum mean square error forecasting technique and employs a base stock policy. With the developed bullwhip effect measure, we investigate the impact of seasonal factor on the bullwhip effect. Then, we prove that seasonal factor plays an important role on the occurrence of the bullwhip effect.

• 동력기계공학회지
• /
• 제11권3호
• /
• pp.3-8
• /
• 2007

The emergency AC power supply system of the nuclear power plant is designed to supply the power to the nuclear reactor at the emergency operating condition. The safety function of the diesel generator at the nuclear power plant is to supply AC electric power to the plant safety system whenever the preferred AC power supply is unavailable. The reliable operation of onsite emergency diesel generator should be ensured by a conditioning monitoring system designed to maintain and monitor and forecast the reliability level of diesel generator. To do this kind of diesel generator condition monitoring we reviewed several operating factors and history of the wolsong unit 3 diesel generator and selected the proper conditioning monitoring operating factors.