• Journal of Korean Institute of Industrial Engineers
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• v.20 no.4
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• pp.135-149
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• 1994

Demand forecasting is to estimate the demand of customers for products and services. Since the future is uncertain in nature, it is too difficult for us to predict exactly what will happen. Therefore, when the forecasting is performed upon the uncertain future, it is realistic to estimate the value of demand as an interval or a fuzzy number instead of a crisp number. In this paper, we propose a demand forecasting method using the standard back-propagation algorithm and then we extend the method to the case of interval inputs. Next, we demonstrate that the proposed method using the interval neural networks can represent the fuzziness of forecasting values as intervals. Last, we propose a demand forecasting method using the transformed input variables that can be obtained by taking account of the degree of influence between an input and an output.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.28 no.2
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• pp.146-151
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• 2005

Some distributions have been used for diagnosing the lead time demand distribution in inventory system. In this paper, we describe the negative binomial distribution as a suitable demand distribution for a specific retail inventory management application. We here assume that customer order sizes are described by the Poisson distribution with the random parameter following a gamma distribution. This implies in turn that the negative binomial distribution is obtained by mixing the mean of the Poisson distribution with a gamma distribution. The purpose of this paper is to give an interpretation of the negative binomial demand process by considering the sources of variability in the unknown Poisson parameter. Such variability comes from the unknown demand rate and the unknown lead time interval.

• International Journal of Concrete Structures and Materials
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• v.10 no.4
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• pp.513-525
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• 2016

The resistance-demand approach has emerged as an effective approach for determining the shear capacity of reinforced concrete beams. This approach is based on the fact that both the shear resistance and shear demand are correlated with flexural tensile strain from compatibility and equilibrium requirements. The basic shear strength, under a given loading is determined from the intersection of the demand and resistance curves. This paper verifies the applicability of resistance-demand procedure for predicting the shear capacity of high strength concrete beams without web reinforcement. A total of 18 beams were constructed and tested in four-point bending up to failure. The test variables included the longitudinal reinforcement ratio, the shear span to depth ratio, and the beam depth. The shear capacity of the beams was predicted using the proposed procedure and compared with the experimental values. The results of the comparison showed good prediction capability and can be useful to design practice.

• The Journal of Korean Academic Society of Nursing Education
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• v.12 no.1
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• pp.95-103
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• 2006

Purpose: This is to find out the correlation between a families burden on a cerebrovascular accident patient and the demand for nursing home. Method: The data was established by using structured questionnaires for 102 nursing families of cerebrovascular accident patient at three university hospitals. Result: 1) The total burden was showed to be at 3.21, which was some what higher than average. Total average of demand for nursing home was at 3.30, which was higher than average. 2) This showed static correlations between the economic, social, physical dependent and psychological burden, and demand for nursing home. The result represents that the higher burden showed a significantly positive correlation to the higher demand for nursing home. Conclusion: If a systemic support of nursing home is prepared the differentiated nursing home matched perfectly on each burden, the burden on a family of the patient can be decreased effectively.

• Journal of Information Technology Services
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• v.10 no.3
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• pp.265-284
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• 2011

The purpose of this study is to analyze the demand for telemedicine and telehealthmanagement services, which are key elements of home based u-health. The conjoint analysis, which is a conventional method for demand analysis for newly introduced products, is employed, utilizing the survey data on 500 seoul citizens. Further, multivariate probit model is used to estimate the demand. The result shows that the demand for telemedicine services is greater than that of telehealthmanagement services. Further, home-based u-health services will play a role as a complementary for face-to-face medical treatments, rather than a substitute. Meanwhile, the demand for home-based u-health services is found to be very sensitive to price.

• IE interfaces
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• v.16 no.4
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• pp.400-410
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• 2003

Most of the demand forecasting which have been studied is about long-term time series over 15 years demand forecasting. In this paper, we set up the most optimal ARIMA model for the short-term time series demand forecasting and suggest demand forecasting system for short-term time series by appraising suitability and predictability. We are going to use the univariate ARIMA model in parallel with the bivariate transfer function model to improve the accuracy of forecasting. We also analyze the effect of advertisement cost, scale of branch stores, and number of clerk on the establishment of marketing policy by applying statistical methods. After then we are going to show you customer's needs, which are number of buying products. We have applied this method to forecast the annual sales of refrigerator in four branch stores of A company.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2003.05a
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• pp.213-217
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• 2003

An Ad-Hoc networks is a set of wireless mobile host which forms temporary networks without any concentrated controls or any helps of standard support services. Mobile host' routers are operated by their mobile hosts without fixed routers, therefore, the original routing protocol algorithm are not effective. There are two major Protocols in Ad-Hoc Network. A Table-Driven algorithm and an On-Demand, but the latter is presented more effective. We try to compare and analyze the performances of each protocol's host in this thesis.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.1
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• pp.20-24
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• 2008

A bid-based pool(BBP) model is representative of energy market structure in a number of restructured electricity markets. Supply function equilibrium(SFE) models of interaction better match what is explicitly required in the bid formats of typical BBP markets. Many of the results in the SFE literature involve restrictive parametrization of the bid cost functions. In the SFE models, two parameters, intercept and slope, are available for strategic bidding. This paper addresses the realistic competition format that players can choose both parameters arbitrarily. In a fixed demand function, equilibrium conditions for generation company's profit maximization have a degree of freedom, which induces multi-equilibrium. So it is hard to choose a convergent equilibrium. However, consideration of stochastic demand function makes the equilibrium conditions independent each other based on the amount of variance of stochastic demand function. This variance provides the bidding players with incentives to change the slope parameter from an equilibrium for a fixed demand function until the slope parameter equilibrium.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.63 no.3
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• pp.189-194
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• 2014

Due to the increasing of power consumption, it is difficult to construct accurate prediction model for daily peak power demand. It is very important work to know power demand in next day for manager and control power system. In this research, we develop a daily peak power demand prediction method based on hybrid type composed of AR and Neuro-Fuzzy model. Using data sets between 2006 and 2010 in Korea, the proposed method has been intensively tested. As the prediction results, we confirm that the proposed method makes it possible to effective estimate daily peak power demand than conventional methods.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.28 no.10
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• pp.43-48
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• 2014

With the energy paradigm shift from supply side management to demand side management, many researches have been done on demand side resource management and demand response. At the same time, Obix, BacNet-WS and OPC-UA are popularly used in buildings and industry energy management system. However, it is not easy to interchange the data and information among the systems cause a variety of protocols are used in buildings and factories. Therefore, in this paper, we are proposing an open business platform not only to integrate and manage the demand resources using various protocols and standards, but also to allow to plug-ins a new business service on top of the platform.