• 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.

• Journal of Korean Institute of Industrial Engineers
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• v.31 no.3
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• pp.210-218
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• 2005

In the current global business environment, it is very important how to allocate products from the producer to buyers (or distributors). Sometimes some buyers can order more than pertinent demand due to inappropriate forecasting customers' orders. This is the big obstacle to the efficient allocation of products. If the producer can become aware of buyers' pertinent demand, it is possible to realize the high-level order fulfillment through the effective allocation of products. In this study, a new allocation policy is proposed considering buyers' demands. The backpropagation algorithm, one of algorithms in neural network theory, is used to find pertinent demands from the distributors' orders. In the experiment, an allocation policy considering buyers' demands outperforms previous allocation policies.

• Journal of the Korean Operations Research and Management Science Society
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• v.29 no.1
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• pp.87-99
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• 2004

In this paper, we have developed a technology-service relationship model which describes the diffusion process of a group of services and relevant technologies, and have applied the developed model to the prediction of the number of subscribers to the next generation mobile service. The technology-service relationship model developed in this paper incorporates the developing process of relevant technologies, a supply-side factor, into the diffusion process of specific services, while many diffusion models and multi-generation diffusion models in previous researches are mainly reflect the demand-side factors. So, the proposed model could effectively applied to the telecommunication services where the developing of the relevant technologies are very essential to the service Penetration. In our application, the Proposed model provides a competitive substitution between the next generation mobile service and the traditional mobile service.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.11
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• pp.5290-5299
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• 2011

The ultimate purpose of this research is to propose a method to improve water supply management efficiency. As an effort to solve this comprehensive problem, the purposes of this paper are summarized into the following two main subjects. One is the development of a series of demand forecasting models targeting for each theme of urban water such as residential, commercial, industrial water. The other is the suggestion on the development and utilization plan of a GIS-based information system where the developed models are incorporated. For these, a series of efforts were performed such as evaluating and choosing of the candidate field areas, selecting a proper sensor and an installation point for each theme. Installed are sensors, a wireless communication infrastructure, and a field data acquisition and management server. Developed are a protocol for the wireless communication and a real-time data monitoring system. Nextly, the urban water facility-related and other necessary data were handled to make those into a series of GIS-ready databases. Finally, a GIS-based management system was designed and a blueprint for the implementation is suggested.

• Journal of Korea Society of Industrial Information Systems
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• v.25 no.2
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• pp.57-72
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• 2020

The price of iron ore has continued to fluctuate with high demand and supply from many countries and companies. In this business environment, forecasting the price of iron ore has become important. This study developed the machine learning model forecasting the price of iron ore a one month after the trading events. The forecasting model used distributed lag model and deep learning models such as MLP (Multi-layer perceptron), RNN (Recurrent neural network) and LSTM (Long short-term memory). According to the results of comparing individual models through metrics, LSTM showed the lowest predictive error. Also, as a result of comparing the models using the ensemble technique, the distributed lag and LSTM ensemble model showed the lowest prediction.

• Korean Journal of Construction Engineering and Management
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• v.8 no.5
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• pp.161-172
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• 2007

By prosperous condition of construction economy in the early 90s in Korea, the government needed a lot of the qualified professional engineers (PE) to manage the construction site. In order to meet the high demand of P.E., Government has established the admitted engineer systems(AES) in 1995 that give the authority of principal engineers to the admitted engineers who do not take the written examination but have equivalent working experience. Since 2000, professional $engineer^{\circ}{\phi}s$ shortage has been resolved. however, the opposite situation, which is serious over-supply of construction engineers has occurred. Thus, Government announced that would abolish the admitted engineer systems as recognized the existent admitted engineers(about 1,000,000 persons) from 2007. However, Professional Engineers Institution has strongly insisted that Government should not recognize existent admitted engineers. From this point of view, it is critical to make the supply-demand forecast systems as a derivative approach of System Dynamics also, that is useful in comparing the argument between Government and Professional Engineers Institution. This paper describes about principal $engineer^{\circ}{\phi}s$ supply change by admitted engineer system abrogation and suggests the idea to regulate the supply and demand with the improvement of the regal system.

• Journal of Korean Society of Water and Wastewater
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• v.11 no.1
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• pp.109-118
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• 1997

In this study, we examined the structural analysis of water demand fluctuation for water distribution control of water supply network. In order to analyze for the length of stationary time series, we calculate autocorrelation coefficient of each case equally divided data size. As a result, it was found that, with the data size of around three months, any case could be used as stationary time series. we analyze cross-correlation coefficient between the daily water consumption's data and primary influence factors. As a result, we have decided to use weather conditions and maximum temperature as natural primary factors and holidays as a social factor. Applying the multiple ARIMA model, we obtains an effective model to describe the daily water demand prediction. From the forecasting result, even though we forecast water distribution quantity of the following year, estimated values well express the flctuations of measurements. Thus, the suitability of the model for practical use can be confirmed. When this model is used for practical water distribution control, water distribution quantity for the following day should be found by inputting maximum temperature and weather conditions obtained from weather forecast, and water purification plants and service reservoirs should be operated based on this information while operation of pumps and valves should be set up. Consequently, we will be able to devise a rational water management system.

• The Proceedings of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.6 no.3
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• pp.43-49
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• 1992

Forecasting of electric power demand has been a basic element for electric power system operation and system development, and it's accuracy has very strong influence on reliability and economical efficience of power supply. So, in this paper, long―term maximum electric power demand has been forecasted by using the triple exponential smoothing method initiated R.G.Brown. It has been regarded this method as high accuracy and operational convenience. The smoothing function is a liner combination of all past observations and the weight given to previous observations decreases geometrically with age.

• Korean Journal of Construction Engineering and Management
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• v.6 no.2 s.24
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• pp.61-68
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• 2005

The analysis described in this paper indicate the existence of a correlationship for housing demand and water supply ratio. Using subjective statistical data for the trend of population on regional area, water supply ratio and the number of households, the paper examines the correlationship of forecasting factors for apartments in the ways in which the tendency of demands for apartments and water supply ratio have been analyzed within small and mediumsized city. Differences in the correlationship on the several scale of a city are also taken into account in the analysis. The summary table of the tendency for housing supplies, population and water supply ratio on each scale of a city was generated using data from LAIB. This study attempted to address certain factors that are measurable within a specified paradigm, in order to investigate the extent to which the expectation of apartment supplies can be estimated from the correlationship of water supply ratio. Therefore, it can be suggested that the limited scale of a city are set to maintain the correlationship for housing demands and water supply ratio.

• Journal of Korea Spatial Information System Society
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• v.11 no.2
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• pp.177-181
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• 2009

Developing u-Public facilities for application u-City is to combine both the state-of-the art of the construction and ubiquitous computing and must be flexibly comprised of the facilities for the basic service of the building such as air conditioning, heating, lighting and electric equipments to materialize a new format of spatial planning and the public facilities inside or outside. Accordingly, in this paper we suggested the time pattern system for predicting the most basic power system loads for the basic service. To application the tim e pattern we applied SOM algorithm and k-means method and then clustered the data each weekday and each time respectively. The performance evaluation results of suggestion system showed that the forecasting system better the ARIMA model than the exponential smoothing method. It has been assumed that the plan for power supply depending on demand and system operation could be performed efficiently by means of using such power load forecasting.