• 한국항해학회지
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• 제8권1호
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• pp.1-16
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• 1984

The economical property of a shipping enterprise, as well as other transportation industries, is determined by the difference between the freight earned and expense paid. This study can be regarded as a division of optimizing ship allocation to routes under the integrated port transport system. Fleet planning and scheduling require complicated allocations of cargoes to ships and ships to routes in order to optimize the given criterion function for a given forecast period. This paper deals with the optimum ship allocation problem minimizing the operating cost of ships in a shipping company. Optimum fleet operating for a shipping enterprise is very important, since the marine transportation is a form of large quantity transport requiring long-term period, and there is a strong possibility to bring about large amount of loss in operation resulting from a faulty ship allocation. Where there are more than one loading and discharging ports, and a variety of ship's ability in speed, capacity, operating cost etc., and when the amount of commodities to be transported between the ports has been determined, then the ship's schedule minimizing the operating cost while satisfying the transport demand within the predetermined period will be made up. First of all a formula of ship allocation problems will be established and then will be constructed to solve an example by the Integer Programming application after consideration of the ship's ability, supply and demand of commodity, amount of commodity to be transported, operating costs of each ship etc. This study will give good information on deciding intention for a ship oprator or owner to meet the computerization current with shiping management.

• 농촌계획
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• 제25권4호
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• pp.109-117
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• 2019

The purpose of this study is to present a time series model of onion and garlic prices. After considering the various time series models, we calculated the appropriate time series models for each item and then selected the model with the minimized error rate by reflecting the monthly dummy variables and import data. Also, we examined whether the predictive power improves when we combine the predictions of the Korea Rural Economic Institute with the predictions of time series models. As a result, onion prices were identified as ARMGARCH and garlic prices as ARXM. Monthly dummy variables were statistically significant for onion in May and garlic in June. Garlic imports were statistically significant as a result of adding imports as exogenous variables. This study is expected to help improve the forecasting model by suggesting a method to minimize the price forecasting error rate in the case of the unstable supply and demand of onion and garlic.

• Environmental Engineering Research
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• 제23권4호
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• pp.406-419
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• 2018

In planning public service systems such as waterworks, the design population is very important factor. Owing to the limitations of the indirect method, two new models, which take into consideration urban characteristics, were developed to accurately predict external migration rate (EMR), which is an essential component in estimating reliably the design population. The root mean square error (RMSE) between the model values and observed values were 10.12 and 15.58 for the metropolitan cities and counties respectively and were lower compared to RMSE values of 27.31 and 28.79 obtained by the indirect method. Thus, the developed models provide a more accurate estimate of EMR than the indirect method. In addition, the major influencing factors for external migration in counties were development type, ageing index, number of businesses. On the other hand, the major influencing migration factors for cities were project scale, distance to city center, manufacturing size, population growth rate and residential environment. Future medium and long-term studies would be done to identify emerging trends to appropriately inform policy making.

• 한국태양에너지학회 논문집
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• 제39권5호
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• pp.29-40
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• 2019

In response to the rapid climate change, in order to save energy in the field of buildings, the country is planning not only zero energy buildings but also zero energy cities. In the Urban Development Project, the Energy Use Plan Report is prepared and submitted by predicting the amount of energy demand at the planning stage. However, due to the activation of zero-energy buildings and the increase in the supply of new and renewable energy facilities, the energy consumption behavior of buildings in the city is changing from the previous ones. In this study, to estimate urban energy demand of Zero Energy City, building energy demand forecasts based on "Passive plans for use of energy based primary energy consumption", "Actual building energy usage data from Korea Appraisal Board" and "data from Certification of Building Energy Efficiency Rating" as well as demand forecast according to existing "Consultation about Energy Use Plan Code" were calculated and then applied to Multifunctional Administrative City 5-1 zone to compare urban total energy demand forecasts.

• 한국의류산업학회지
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• 제23권4호
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• pp.480-490
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• 2021

Sales forecasting is crucial for many retail operations. For apparel retailers, accurate sales forecast for the next season is critical to properly manage inventory and plan their supply chains. The challenge in this increases because apparel products are always new for the next season, have numerous variations, short life cycles, long lead times, and seasonal trends. In this study, a sales forecasting model is proposed for apparel products using machine learning techniques. The sales data pertaining to outerwear items for four years were collected from a Korean sports brand and filtered with outliers. Subsequently, the data were standardized by removing the effects of exogenous variables. The sales patterns of outerwear items were clustered by applying K-means clustering, and outerwear attributes associated with the specific sales-pattern type were determined by using a decision tree classifier. Six types of sales pattern clusters were derived and classified using a hybrid model of clustering and decision tree algorithm, and finally, the relationship between outerwear attributes and sales patterns was revealed. Each sales pattern can be used to predict stock-keeping-unit-level sales based on item attributes.

• 대한건축학회논문집:구조계
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• 제34권11호
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• pp.73-79
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• 2018

In this study, for the prediction of energy consumption in the ventilator, one of the components of the air conditioning system, the predicted results were analyzed and accurate by the change in the number of neurons and inputs. The input variables of the prediction model for the energy volume of the fan were the supply air flow rate, the exhaust air flow rate, and the output value was the energy consumption of the fan. A predictive model has been developed to study with the Levenbarg-Marquardt algorithm through 8760 sets of one-minute resolution. Comparison of actual energy use and forecast results showed a margin of error of less than 1% in all cases and utilization time of less than 3% with very high predictability. MBE was distributed with a learning period of 1.7% to 2.95% and a service period of 2.26% to 4.48% respectively, and the distribution rate of ${\pm}10%$ indicated by ASHRAE Guidelines 14 was high.8.

• 농업과학연구
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• 제48권2호
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• pp.311-331
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• 2021

Climate change with extreme hydrological events has become a significant concern for agricultural water systems. Climate change affects not only irrigation availability but also agricultural water requirement. In response, adaptation strategies with soft and hard options have been considered to mitigate the impacts from climate change. However, their implementation has become progressively challenging and complex due to the interconnected impacts of climate change with socio-economic change in agricultural circumstances, and this can generate more uncertainty and complexity in the adaptive management of the agricultural water systems. This study was carried out for the agricultural water supply system in Seongju dam watershed in Seonju-gun, Gyeongbuk in South Korea. The first step is to identify system disturbances. Climate variation and socio-economic components with historical and forecast data were investigated Then, as the second step, problematic trends of the critical performance were identified for the historical and future climate scenarios. As the third step, a system structure was built with a dynamic hypothesis (causal loop diagram) to understand Seongju water system features and interactions with multiple feedbacks across system components in water, agriculture, and socio-economic sectors related to the case study water system. Then, as the fourth step, a mathematical SD (system dynamics) model was developed based on the dynamic hypothesis, including sub-models related to dam reservoir, irrigation channel, irrigation demand, farming income, and labor force, and the fidelity of the SD model to the Seongju water system was checked.

• 대한안전경영과학회지
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• 제24권2호
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• pp.127-134
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• 2022

Production management in the automobile parts industry is carried out according to the production plan of the customer, so it is important to prevent shortages in product supply. As the product composition became increasingly complex, the MES System was built for the purpose of efficient production plan management and inventory management, but its utilization is low. This study analyzed the problems of the MES system and sought to improve it. Through previous studies, it was confirmed that the inventory management of the pull approach that actually occurred in the warehouse is more suitable than the push approach based on the forecast of the warehouse for the volatility, complexity, and uncertainty of orders in the auto parts industry. To realize this, we tried distributed MRP by using the ADO function of VBA to link the standard information of the MES system with Excel and change the structure of the BOM table. Through this, it can help increase the accuracy of production planning and realize efficient inventory management, thereby increasing the utilization of the MES system in the auto parts industry and enhancing the competitiveness of the company.

• 분석과 대안
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• 제4권2호
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• pp.71-102
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• 2020

This study analyzes the effect of demographic changes on economic growth. We use the supply-side output identity to forecast the growth potential of the Korean economy. According to the results, even based on optimistic assumptions and prospects, the economic growth rate is likely to fall drastically starting in 2020. Of course, to maintain growth potential, efforts to increase productivity are necessary. However, given the historical experience of developed countries, it is not clear whether the huge trend of demographic change can be offset by efforts to increase productivity. In the so-called '30-50 club' countries, both labor productivity and growth rate tend to fall after reaching the per capita income of $30,000. The degree of decline in the growth rate is closely related to changes in the working age population and the prime-age workforce. The results are similar when tracking the path of changes in total factor productivities of the economy. When a certain level of income is reached, the increase in total factor productivity also tends to slow down. The ripple effects of rapid changes in demographics will indeed be extensive. The negative impact is likely to be concentrated at a time when the working age population, the prime-age workforce, and the total population shrink simultaneously. Above all, it is necessary to use the government's fiscal space to block the possibility of a rapid fall in the growth rate. In addition, it is important to continuously implement various reform tasks that should be promoted, such as improving the education system and strengthening the social safety net.

• 한국융합학회논문지
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• 제12권5호
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• pp.173-183
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• 2021

본 연구는 광주광역시에서 소비활동을 하는 친환경 소비자의 인식도 및 구매행동에 대한 융합적 연구이다. 광주광역시에서 소비활동을 하는 사람 151명을 대상으로 설문조사를 실시하여 빈도분석, 기술통계분석, 주성분분석, 상관관계분석을 실시하였다. 인지도, 관심도, 만족도에 대한 융합적 연구로 친환경 소비자의 인식도 및 구매행동이 융합적 친환경 농산물 소비까지 친환경 소비시장에 대한 공급적인 측면의 미래예측 자료로 사용할 수 있으며, 친환경 소비시장의 흐름 및 전체를 추론해 보는 소비자의 소중한 자료의 일부로 사용될 수 있을 것이다.