• International conference on construction engineering and project management
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• 2005.10a
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• pp.952-955
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• 2005

In the early 90's, we had serious shortage of construction engineers in Korea. The shortage was acute especially in construction quality control and supervision area, which were gaining social attention due to the road bridge and the department store collapse that took the hundreds of lives in the early 90's in Seoul, Korea. In order to meet the high demand of construction engineers, the engineering license regulations were changed in 1995. Engineers who did not pass the written exam but have equivalent working experience are given engineering license to practice engineering legally. Since year 2000, while the severe engineer-shortage has been resolved, the opposite situation has occurred: there is serious over-supply of construction engineers. Policy makers and engineering practitioners are agreed to bring back the old-fashioned written exam engineer licensing system like before 1995, i.e., no more written exam exemption. However, the engineers who obtained license without taking written exam may not want to go back to old policy which would take their license. It is required to provide appropriate grace period before the new policy takes effect to minimize the impact of the changes. This paper forecasts the supply-demand of construction engineers providing the basis for the most appropriate policy changes.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2001.12a
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• pp.27-30
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• 2001

A inventory management system of the manufacturing industry has a model of different kinds according to the objective and the situation. A inventory management system needs superior system technique in demand forecast, economical efficiency, reliability and application for stable supply of the finished goods, the raw materials and the parts. This paper proposes a demand forecast method based on fuzzy structured neural network, which uses min-operation and trapezoid membership function of fuzzy rules. So we can have an intelligent inventory management system for optimized decision-making of forecasting data with expert's opinion in fuzzy environment. This inventory management system used an intelligence agent and it could be adapted to asystemenvironmentchangeinorder.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.7
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• pp.584-590
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• 2001

An inventory management system of manufacturing industry has a model of different kinds according to the objective and the situation. An inventory management system needs superior system technique in demand forecast, economical efficiency, reliability and application for stable supply of the finished goods, the raw materials and the parts. This paper proposes a demand forecast method based on fuzzy structured neural network, which uses min-operation and trapezoid membership function of fuzzy rules. So we can construct an intelligent inventory management system that make optimized decision-making for forecasting data with expert s opinion in fuzzy environment. The inventory management system uses intelligence agent and it could be adapted to a system environment change in order.

• Korean Journal of Agricultural Science
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• v.16 no.1
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• pp.71-83
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• 1989

The purpose of this research are to forecast the demand and supply of milk in Korea, and to obtain information for attitudes affecting milk consumption, which is necessary to make a plan for increasing milk consumption in Korea. The estimation of the milk demand and production was made by the multiplicative decomposition method and the statistical function. Data on consumer were collected from 737 students who were attending primary school, middle school and university in Daejeon during the period of July 11 to July 21, 1988. The results obtained are as follows; 1. The prediction results showed that the production for milk will over supply 21,900 tons in 1,990, 70,800 tons in 1,995 by the multiplicative decomposition method and 45,400 tons in 1990, -51,500 tons in 1995 by the statistical function. 2. It was found that almost all the students awared milk as essential food-stuff of common food stuff for the Koreans. 3. Quite a few students were apt to believe that milk processors added water into fluid milk. 4. Most students showed obtaining information about the nutritional value of milk by school education and advertising of TV, Radio, and Printed media. 5. However, it was found that the advertising by TV, Radio, and Printed media did hardly give to consumers influences on the choice of a particular milk brand. Accordingly, the conclusions are as follows; 1. Need to provide consumers with well planned education programs on the nutritional value of milk. 2. Heavy brand advertising for fluid milk may mislead the understanding of consumer, since city milk is not much differentiated in Korea. Therefore the milk processors should put more efforts in generic milk promotion by reducing brand advertizement. 3. The milk processors should provide major portion of financing for generic milk promotion program.

• Journal of Korean Society of Water and Wastewater
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• v.25 no.4
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• pp.581-589
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• 2011

Generally, treated water or raw water is transported into storage reservoirs which are receiving facilities of local governments from multi-regional water supply systems. A water supply control and operation center is operated not only to manage the water facilities more economically and efficiently but also to mitigate the shortage of water resources due to the increase in water consumption. To achieve the goal, important information such as the flow-rate in the systems, water levels of storage reservoirs or tanks, and pump-operation schedule should be considered based on the resonable water demand forecasting. However, it is difficult to acquire the pattern of water demand used in local government, since the operating information is not shared between multi-regional and local water systems. The pattern of water demand is irregular and unpredictable. Also, additional changes such as an abrupt accident and frequent changes of electric power rates could occur. Consequently, it is not easy to forecast accurate water demands. Therefore, it is necessary to introduce a short-term water demands forecasting and to develop an application of the forecasting models. In this study, the forecasting simulator for water demand is developed based on mathematical and neural network methods as linear and non-linear models to implement the optimal water demands forecasting. It is shown that MLP(Multi-Layered Perceptron) and ANFIS(Adaptive Neuro-Fuzzy Inference System) can be applied to obtain better forecasting results in multi-regional water supply systems with a large scale and local water supply systems with small or medium scale than conventional methods, respectively.

• Journal of Internet Computing and Services
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• v.16 no.2
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• pp.99-107
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• 2015

In this era of smart convergent environment wherein all industries are converged on ICT infrastructure and industries and cultures come together, the information and communication construction business is becoming more important. For the information and communication construction business to continue growing, it is very important to ensure that technical manpower is stably supplied. To date, however, there has been no theoretically methodical analysis of manpower supply and demand in the information and communications construction business. The need for the analysis of manpower supply and demand has become even more important after the government announced the road map for the development of construction business in December 2014 to seek measures to strengthen the human resources capacity based on the mid- to long-term manpower supply and demand analysis. As such, this study developed the manpower supply and demand forecast model for the information and communications construction business and presented the result of manpower supply and demand analysis. The analysis suggested that an overdemand situation would arise since the number of graduates of technical colleges decreased beginning 2007 because of fewer students entering technical colleges and due to the restructuring and reform of departments. In conclusion, it cited the need for the reeducation of existing manpower, continuous upgrading of professional development in the information and communications construction business, and provision of various policy incentives.

• Journal of Environmental Science International
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• v.22 no.8
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• pp.965-977
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• 2013

Reliable long-term streamflow forecasting is invaluable for water resource planning and management which allocates water supply according to the demand of water users. It is necessary to get probabilistic forecasts to establish risk-based reservoir operation policies. Probabilistic forecasts may be useful for the users who assess and manage risks according to decision-making responding forecasting results. Probabilistic forecasting of seasonal inflow to Andong dam is performed and assessed using selected predictors from sea surface temperature and 500 hPa geopotential height data. Categorical probability forecast by Piechota's method and logistic regression analysis, and probability forecast by conditional probability density function are used to forecast seasonal inflow. Kernel density function is used in categorical probability forecast by Piechota's method and probability forecast by conditional probability density function. The results of categorical probability forecasts are assessed by Brier skill score. The assessment reveals that the categorical probability forecasts are better than the reference forecasts. The results of forecasts using conditional probability density function are assessed by qualitative approach and transformed categorical probability forecasts. The assessment of the forecasts which are transformed to categorical probability forecasts shows that the results of the forecasts by conditional probability density function are much better than those of the forecasts by Piechota's method and logistic regression analysis except for winter season data.

• Journal of Korean Society of Transportation
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• v.24 no.7 s.93
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• pp.91-100
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• 2006

Travel Demand Forecasting (TDF) is an essential and critical process in the evaluation of the highway improvement Project. The four-step TDF Process has generally been used to forecast travel demand and analyze the effects of diverted travel demand based on the given Origin-Destination trips in the future. Transportation system improvements, however, generate more travel, Induced Travel Demand (ITD) or latent travel demand, which has not been considered in the project evaluation. The Purpose of this study Is to develop a model which can forecast the ITD applied theory of economics and the Program(I.D.A) which can be widely applied to project evaluation analysis. The Kang-Byun-Book-Ro expansion scenario is used to apply and analyze a real-world situation. The result highlights that as much as 15% of diverted travel demand is generated as ITD. The results of this study are expected to improve reliability of the project evaluation of the highway improvement Project.

• The Journal of Bigdata
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• v.5 no.2
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• pp.17-27
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• 2020

District heating system supplies heat from low-cost high-efficiency heat production facilities to heat demand areas through a heat pipe network. For efficient heat supply system operation, it is important to accurately predict the heat demand within the region and optimize the heat production plan accordingly. In this study, a heat demand forecasting model is proposed considering real-time calorimeter information from local heat demands. Previous models considered ambient temperature and heat demand history data to predict future heat demands. To improve forecast accuracy, the proposed heat demand forecast model added big data from real-time calorimeters installed in the heat demands within the target region. By employing calorimeter information directly in the model, it is expected that the proposed forecast model is to reflect heat use pattern of each demand. Computational experiemtns based on the actual heat demand data shows that the forecast accuracy of the proposed model improved when the calorimeter big data is reflected.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.144-144
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• 2021

The rapid urbanization in many Asian countries has taken millions of people from the rural countryside to concentrated megacities, which eventually putting pressure on the existing water resources. The over-growing population and increasing living standard of people in the urban region of developed as well as developing countries such as Korea, China, Japan and India have witnessed a drastic change in terms of domestic water demand for the past few decades. In this study, we used the concept of potential surface water availability in the form of surface runoff for future vulnerability assessment. We focused on 42 megacities having population more than 5 million as per the United Nations (UN) census data 2020. The study shows that 30 out of 42 cities having more than 180L/p/d demand for domestic use based on various references. We have predicted the domestic water demand for all the cities on the basis of current per capita demand up to 2035 using UN projected population data. We found that the projected water demand in megacities such as Seoul, Busan, Shanghai, Ghuanzou are increasing because of high population as well as GDP growth rate. On the contrary, megacities of Japan considered in our stud shows less water demand in future due to decreasing trend of population. As per the past records provided by the local municipalities/authorities, we projected different scenarios based on the future supply for various megacities such as Chennai, Delhi, Karachi, Mumbai, Shanghai, Wuhan, etc. We found that the supply to demand ratio of these cities would be below 75% for future period and if such trend continues then the inhabitants will face serious water stress conditions. Outcomes of this study would help the local policy makers to adopt sustainable initiatives on urban water governance to avoid the severe water stress conditions in the vulnerable megacities.