• Title/Summary/Keyword: demand parameter

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Modeling Procedure to Adapt to Change of Trend of Water Demand: Application of Bayesian Parameter Estimation (물수요의 추세 변화의 적응을 위한 모델링 절차 제시:베이지안 매개변수 산정법 적용)

  • Lee, Sangeun;Park, Heekyung
    • Journal of Korean Society of Water and Wastewater
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    • v.23 no.2
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    • pp.241-249
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    • 2009
  • It is well known that the trend of water demand in large-size water supply systems has been suddenly changed, and many expansions of water supply facilities become unnecessary. To be cost-effective, thus, politicians as well as many professionals lay stress on the adaptive management of water supply facilities. Failure in adapting to the new trend of demand is sure to be the most critical reason of unnecessary expansions. Hence, we try to develop the model and modeling procedure that do not depend on the old data of demand, and provide engineers with the fast learning process. To forecast water demand of Seoul, the Bayesian parameter estimation was applied, which is a representative method for statistical pattern recognition. It results that we can get a useful time-series model after observing water demand during 6 years, although trend of water demand were suddenly changed.

Diagnosis of Lead Time Demand Based on the Characteristics of Negative Binomial Distribution (음이항분포의 특성을 이용한 조달기간 수요 분석)

  • Ahn Sun-Eung;Kim Woo-Hyun
    • 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.

Supply Function Nash Equilibrium Considering Stochastic Demand Function (확률적 수요함수를 고려한 공급함수의 전략변수 내쉬균형 연구)

  • Lee, Kwang-Ho
    • 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.

Diagnosis of Lead Time Demand Based on the Characteristics of Negative Binomial Distribution (음이항분포의 특성을 이용한 조달기간 수요 분석)

  • Ahn, Sun-Eung;Kim, Woo-Hyun
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.28 no.4
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    • pp.79-84
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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.

Parameter estimation of the Diffusion Model for Demand Side Management Monitoring System (DSM Monitoring을 위한 확산 모델의 계수 추정)

  • Choi, Cheong-Hun;Jeong, Hyun-Su;Kim, Jin-O
    • Proceedings of the KIEE Conference
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    • 1998.07c
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    • pp.1073-1075
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    • 1998
  • This paper presents the method of parameter estimation of diffusion model for monitoring Demand-Side Management Program. Bass diffusion model was applied in this paper, which has different values according to parameters ; coefficients of innovation, imitation and potential adopters. Though it is very important to estimate three parameter, there are no empirical results in practice. Thus, this paper presents the method of parameter estimation in case of few data with constraints to reduce the possibility of bad estimation. The constraints are empirical results or expert's decision. Case studies show the diffusion curves of high-efficient lighting and also forecasting of the peak value for power demand considering diffusion of high-efficient lighting, the feedback and least-square parameter estimation method used in this paper enable us to evaluate the status and forecasting of the effect of DSM program.

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Parameter Estimation of the Diffusion Model for Demand Side Management Monitoring System (DSM 모니터링을 위한 확산 모형의 계수 추정)

  • Kim, Jin-O;Choi, Cheong-Hun;Kim, Jung-Hoon;Lee, Chang-Ho;Kim, Chang-Seob
    • The Transactions of the Korean Institute of Electrical Engineers A
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    • v.48 no.10
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    • pp.1183-1189
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    • 1999
  • This paper presents the method of parameter estimation of diffusion model for monitoring Demand-Side Management program. Bass diffusion model was applied in this paper, which has different values according to the following parameters; coefficients of innovation, imitation and potential adopters. Though it is very important to estimate three parameters precisely, there has been no empirical way in practice. Thus, this paper presents the method of parameter estimation in case of few data with constraints to reduce the possibility of bad estimation. The constraints can be empirical results or expert's decision. Case studies show the diffusion curves and forecasted values of the peak for the high-efficient lighting. The feedback and nonlinear least-square parameter estimation methods used in this paper enable us to evaluate the status and to predict the effect of DSM program.

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Parameter Estimation & Validation of Volume-delay Function based on Traffic Survey Data (교통조사를 통한 도로통행비용함수 구축 및 검증)

  • Kim, Ju-Yeong;Chu, Sang-Ho;Gang, Min-Gu;Heo, Heon
    • Journal of Korean Society of Transportation
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    • v.28 no.1
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    • pp.115-124
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    • 2010
  • VDF(volume-delay function) is one of the most important factor to improve the reliability of traffic demand estimation because it is for estimation of link travel time based on the traffic volume variation. Because VDF of link except for freeway is applied as the parameter of BPR(bureau of public road) of U.S., it causes to deteriorate the accuracy of traffic demand estimation. The purpose of this paper is to establish new parameter of VDF based on the real-surveyed traffic data in order to improve the problem of the existing VDF. We suggest the reclassification of road hierarchy, the approach of traffic survey, the estimating method of VDF parameter, and the improvements of new VDF application. The new VDF allows us to estimate more realistic traffic situation in parts of demand, travel time and path between origin-destination.

Robustness of Bayes forecast to Non-normality

  • Bansal, Ashok K.
    • Journal of the Korean Statistical Society
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    • v.7 no.1
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    • pp.11-16
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    • 1978
  • Bayesian procedures are in vogue to revise the parameter estimates of the forecasting model in the light of actual time series data. In this paper, we study the Bayes forecast for demand and the risk when (a) 'noise' and (b) mean demand rate in a constant process model have moderately non-normal probability distributions.

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Uncertainty of Water Supply in Agricultural Reservoirs Considering the Climate Change (미래 기후변화에 따른 농업용 저수지 용수공급의 불확실성)

  • Nam, Won-Ho;Hong, Eun-Mi;Choi, Jin-Yong
    • Journal of The Korean Society of Agricultural Engineers
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    • v.56 no.2
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    • pp.11-23
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    • 2014
  • The impact and adaption on agricultural water resources considering climate change is significant for reservoirs. The change in rainfall patterns and hydrologic factors due to climate change increases the uncertainty of agricultural water supply and demand. The quantitative evaluation method of uncertainty based on agricultural water resource management under future climate conditions is a major concern. Therefore, it is necessary to improve the vulnerability management technique for agricultural water supply based on a probabilistic and stochastic risk evaluation theory. The objective of this study was to analyse the uncertainty of water resources under future climate change using probability distribution function of water supply in agricultural reservoir and demand in irrigation district. The uncertainty of future water resources in agricultural reservoirs was estimated using the time-specific analysis of histograms and probability distributions parameter, for example the location and the scale parameter. According to the uncertainty analysis, the future agricultural water supply and demand in reservoir tends to increase the uncertainty by the low consistency of the results. Thus, it is recommended to prepare a resonable decision making on water supply strategies in terms of using climate change scenarios that reflect different future development conditions.

A new practical equivalent linear model for estimating seismic hysteretic energy demand of bilinear systems

  • Samimifar, Maryam;Massumi, Ali;Moghadam, Abdolreza S.
    • Structural Engineering and Mechanics
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    • v.70 no.3
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    • pp.289-301
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    • 2019
  • Hysteretic energy is defined as energy dissipated through inelastic deformations during a ground motion by the system. It includes frequency content and duration of ground motion as two remarkable parameters, while these characteristics are not seen in displacement spectrum. Since maximum displacement individually cannot be the appropriate criterion for damage assessment, hysteretic energy has been evaluated in this research as a more comprehensive seismic demand parameter. An innovative methodology has been proposed to establish a new equivalent linear model to estimate hysteretic energy spectrum for bilinear SDOF models under two different sets of earthquake excitations. Error minimization has been defined in the space of equivalent linearization concept, which resulted in equivalent damping and equivalent period as representative parameters of the linear model. Nonlinear regression analysis was carried out for predicting these equivalent parameter as a function of ductility. The results also indicate differences between seismic demand characteristics of far-field and near-field ground motions, which are not identified by most of previous equations presented for predicting seismic energy. The main advantage of the proposed model is its independency on parameters related to earthquake and response characteristics, which has led to more efficiency as well as simplicity. The capability of providing a practical energy based seismic performance evaluation is another outstanding feature of the proposed model.