• 산업공학
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• 제17권spc호
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• pp.79-89
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• 2004

Supply Chain (SC) can balance demands with supply activities as executing Supply Chain Planning (SCP). The fluctuated demands, however, will break the balance between demand and supply. It means that the present SCP is useless in responding the changed demands. Thus it is necessary for SCP to be updated with changed demands. We call this procedure as Supply Chain Replanning. However, the existing measures for SC can not deal with the balance between supply and demand so that they can not detect effectively the timing of replanning. For this reason, a new performance measure, Balancing Point, is developed using momentum, a concept of Physics. It can treat the balance between supply and demand. Also, a replanning method based on Balancing Point is proposed. The proposed method is more effective than the existing replanning method, periodic replanning method and net inventory method.

• 대한임베디드공학회논문지
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• 제5권4호
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• pp.225-233
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• 2010

In this paper, we try to improve the performance of the demand paging loader suggested to use the demand paging way that is not based on operating system. The demand paging switching strategy used in the existing operating system can know the recently used pages by running multi-processing. Then, based on it, some page switching strategies have been made for the recently used pages or the frequently demanded pages. However, the strategies based on operating system cannot be applied in single processing that is not based on operating system because any context switching never occur on the single processing. So, this paper is trying to suggest the demand paging switching strategies that can be applied in paging loader running in single process. In the Return-Prediction-Algorithm, we saw the improved performance in the program that the function call occurred frequently in a long distance. And then, in the Most-Frequently-Used-Page-Remain-Algorithm, we saw the improved performance in the program that the references frequently occurred for the particular pages. Likewise, it had an enormous effect on keeping the memory reduction performance by the demand paging and reducing the running time delay at the same time.

• 산업공학
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• 제24권4호
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• pp.351-361
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• 2011

Forecasting of electricity demand have difficulty in adapting to abrupt weather changes along with a radical shift in major regional and global climates. This has lead to increasing attention to research on the immediate and accurate forecasting model. Technically, this implies that a model requires only a few input variables all of which are easily obtainable, and its predictive performance is comparable with other competing models. To meet the ends, this paper presents an energy demand forecasting model that uses the variable selection or extraction methods of data mining to select only relevant input variables, and employs support vector regression method for accurate prediction. Also, it proposes a novel performance measure for time-series prediction, shift index, followed by description on preprocessing procedure. A comparative evaluation of the proposed method with other representative data mining models such as an auto-regression model, an artificial neural network model, an ordinary support vector regression model was carried out for obtaining the forecast of monthly electricity demand from 2000 to 2008 based on data provided by Korea Energy Economics Institute. Among the models tested, the proposed method was shown promising results than others.

• 대한교통학회지
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• 제19권1호
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• pp.77-88
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• 2001

현재까지의 관측교통량기반 수요추정법은 단일차종(singleclass)기반 연구가 대부분을 차지하고 있다. 그러나 현실 교통망에서는 여러 차종이 혼재되어 교통수요나 흐름을 만든다. 즉, 기존의 관측교통량기반 수요추정법은 PCE(Passenger Car Equivalent) 환산을 통한 여러 개의 차종O/D 및 관측교통량을 승용차 단위로 전환하여 하나의 O/D 및 관측교통량으로 만들어 O/D를 추정하고, 최초의 PCE환산이전 차종별 O/D의 고정비율과 관측교통량 고정비율로 곱해 차종별 O/D 및 관측교통량으로 나누어 분석하는 것이 일반적인 방법이었다. 즉, 다차종기반분석법은 각각의 차종별 O/D에 대한 노선선택비율을 각각 계산하고, 그에 따른 목적함수 감소방향인 gradient를 또한 각각 계산하여 차종별 추정력을 극대화하는 것이 그 장점이라고 할 수 있다. 따라서, 본 연구에서는 단일차종기반추정법을 다차종기반추정법으로 확장하여 차종간 혼잡을 고려한 보다 현실적인 수요추정기법을 마련하는 것이 본 연구의 목적이라고 하겠다.

• Journal of Information Processing Systems
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• 제19권2호
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• pp.258-266
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• 2023

Aiming at the problems of poor customer satisfaction and poor accuracy of customer classification, this paper proposes a customer classification model based on speech recognition. First, this paper analyzes the temporal data characteristics of customer demand data, identifies the influencing factors of customer demand behavior, and determines the process of feature extraction of customer voice signals. Then, the emotional association rules of customer demands are designed, and the classification model of customer demands is constructed through cluster analysis. Next, the Euclidean distance method is used to preprocess customer behavior data. The fuzzy clustering characteristics of customer demands are obtained by the fuzzy clustering method. Finally, on the basis of naive Bayesian algorithm, a customer demand classification model based on speech recognition is completed. Experimental results show that the proposed method improves the accuracy of the customer demand classification to more than 80%, and improves customer satisfaction to more than 90%. It solves the problems of poor customer satisfaction and low customer classification accuracy of the existing classification methods, which have practical application value.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회 1998년도 추계학술대회 논문집
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• pp.245-248
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• 1998

In this paper, as a forecasting method, the market survey for forecasting demand is introduced for the estimation of subscriber line demand in the optical access networks. The market survey method for the new multimedia services is attempted to collect information directly from customers using the questionnaires for home-users and business-users in local loops. Analysis rationale of questionnaires is suggested to estimate the number of subscriber lines. Also, two measures are presented to quantify the credibility on survey responses; one is the probability that the customer will use the multimedia services and the other is the rate that the subscriber line demand will be actually realized. The former measure is calculated based on the information on customers and the Logit analysis. The latter is obtained by the degree of customer's knowledge about specific services and the customer's willingness to use the services. Based on the values of two measures, the number of subscriber line demand can be developed for installing the optical access networks.

• 조명전기설비학회논문지
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• 제29권5호
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• pp.86-93
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• 2015

Recently, ESS became efficient device to stabilize electric power supply system with the development SG related technology. In fact. there are some constraints to supply ESS, because of the high cost and required space, but rapid technology development for ESS will make it more useful soon. So, through this paper, we analyzed the benefit and demand effect when the battery is applied the building based on the measured energy consumption. After that, we got the conclusion that there is a volume limit in ESS application, in a benefit view point. And we realized that there is a demand violation, and the Cost-based BEMS is the best solution to enhance the effect of ESS application.

• 전기학회논문지
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• 제58권1호
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• pp.1-6
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• 2009

The traditional demand prediction was based on the technique wherein electric power corporations made monthly or seasonal estimation of electric power consumption for each area and subscription type for the next one or two years to consider both seasonally generated and local consumed amounts. Note, however, that techniques such as pricing, power generation plan, or sales strategy establishment were used by corporations without considering the production, comparison, and analysis techniques of the predicted consumption to enable efficient power consumption on the actual demand side. In this paper, to calculate the predicted value of electric power consumption on a short-term basis (15 minutes) according to the amount of electric power actually consumed for 15 minutes on the demand side, we performed comparison and analysis by applying a 15-minute interval prediction technique to the average and that to the time series analysis to show how they were made and what we obtained from the simulations.

• 대한인간공학회지
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• 제24권1호
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• pp.9-17
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• 2005

81.1% of traffic accidents is attributed to the drivers. In this regard, D/E model is a practical and effective method in terms of the cost and time in evaluating the road hazardousness. To examine the validity of the threshold values by the levels of demand We selected 10 subjects and collected their physiological signals while they were driving on Honam Highway (Jeonju ${\leftrighttarro}$ Hoideog section). Based on the collected data, the hazardous road condition was evaluated using the new threshold values of the effort level determined by cluster analysis. In applying the D/E model, a decision method based on the demand level was suggested, using a traffic accident prediction model. Additionally, the limit value of the effort level was determined using the drivers' physiological signal data collected at the highway. A comparison analysis of the two D/E models revealed no significant difference: The existing method and the clustering method determined 9 and 7 hazardous road zones, respectively, while actual traffic accidents were reported in 6 and 4 zones, respectively among the predicted road hazardous zones. However, the latter method suggested a more scientific and rational basis in determining the limit value of the Effort level. In conclusion, although D/E model has a great merit as a pioneering method to reflect human factors in evaluating the road hazardousness, it is believed that this method could be improved by a more dynamic method that considers the traffic conditions and the individual physiological signal of the drivers simultaneously in determining a better limit.

• Journal of Information Technology Applications and Management
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• 제24권2호
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• pp.81-96
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• 2017

Forecasting long-term mobile service demand is inevitable to establish an effective frequency management policy despite the lack of reliability of forecast results. The statistical forecasting method has limitations in analyzing how the forecasting result changes when the scenario for various drivers such as consumer usage pattern or market structure for mobile communication service is changed. In this study, we propose a dynamic model of the mobile communication service market using system dynamics technique and forecast the future demand for long-term mobile communication subscriber based on the dynamic model, and also experiment on the change pattern of subscriber demand under various scenarios.