• Proceedings of the KSR Conference
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• 2003.10b
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• pp.3-7
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• 2003

It is very difficult to find optimal train operation plan when analyzing the economic investment using traditional railroad travel demand estimation method. Train operation plan depends on travel demand and vice versa. To solve this problem, this study suggests a demand estimation method to address an optimal train operation scheme with the modal spilt using initial train operation plan and trip assignment.

• Structural Engineering and Mechanics
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• v.60 no.6
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• pp.1021-1038
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• 2016

Considerable part of reinforced concrete building has suffered from destructive earthquakes in Turkey. This situation makes necessary to determine nonlinear behavior and seismic performance of existing RC buildings. Inelastic response of buildings to static and dynamic actions should be determined by considering both flexural plastic hinges and brittle shear hinges. However, shear capacities of members are generally neglected due to time saving issues and convergence problems and only flexural response of buildings are considered in performance assessment studies. On the other hand, recent earthquakes showed that the performance of older buildings is mostly controlled by shear capacities of members rather than flexure. Demand estimation is as important as capacity estimation for the reliable performance prediction in existing RC buildings. Demand estimation methods based on strength reduction factor (R), ductility (${\mu}$), and period (T) parameters ($R-{\mu}-T$) and damping dependent demand formulations are widely discussed and studied by various researchers. Adopted form of $R-{\mu}-T$ based demand estimation method presented in Eurocode 8 and Turkish Earthquake Code-2007 and damping based Capacity Spectrum Method presented in ATC-40 document are the typical examples of these two different approaches. In this study, eight different existing RC buildings, constructed before and after Turkish Earthquake Code-1998, are selected. Capacity curves of selected buildings are obtained with and without considering the brittle shear capacities of members. Seismic drift demands occurred in buildings are determined by using both $R-{\mu}-T$ and damping based estimation methods. Results have shown that not only capacity estimation methods but also demand estimation approaches affect the performance of buildings notably. It is concluded that including or excluding the shear capacity of members in nonlinear modeling of existing buildings significantly affects the strength and deformation capacities and hence the performance of buildings.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 2000.10a
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• pp.114-119
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• 2000

To estimate Agricultural water demand, many factors such as weather, type of crop, soil, cultivation method, crop coefficient and cultivation area, etc. must be considered. But it is not easy to estimate water demand in consideration of these many factors, which are variable according to a period and regional environment. So, this study provides estimation system for agricultural water demand(ESAD) in order to estimate water demand easily and accurately, calculates the present and future agricultural water demand and arranges all factors needed for water demand estimation. This study calibrates the application of estimation system for agricultural water demand with the data observed in the other Studies and analyzes agricultural water demand nationwide.

• 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.

• Earthquakes and Structures
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• v.26 no.2
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• pp.117-130
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• 2024

Probabilistic model of seismic demand is the main tool used for seismic demand estimation, which is a fundamental component of the new performance-based design method. This model seeks to mathematically relate the seismic demand parameter and the ground motion intensity measure. This study is intended to use Bayesian analysis to evaluate the accuracy of the seismic demand estimation of Steel moment resisting frames (SMRFs) through a completely Bayesian method in statistical calculations. In this study, two types of intensity measures (earthquake intensity-related indices such as magnitude and distance and intensity indices related to ground motion and spectral response including peak ground acceleration (PGA) and spectral acceleration (SA)) have been used to form the models. In addition, an extensive database consisting of sixty accelerograms was used for time-series analysis, and the target structures included five SMRFs of three, six, nine, twelve and fifteen stories. The results of this study showed that for low-rise frames, first mode spectral acceleration index is sufficient to accurately estimate demand. However, for high-rise frames, two parameters should be used to increase the accuracy. In addition, adding the product of the square of earthquake magnitude multiplied by distance to the model can significantly increase the accuracy of seismic demand estimation.

• Journal of the Korean Association of Geographic Information Studies
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• v.10 no.2
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• pp.11-22
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• 2007

This paper is to discuss analytical techniques to estimate demand sizes and volumes that determine optimal locations for multiple facilities for a given services. While demand size estimation is a core part of location modeling to enhance solution quality and practical applicability, the estimation method has been used in limited and restrict parts such as a single population centroid in a given larger census boundary area or small theoretical application experiments(e.s. census track and enumeration district). Therefore, this paper strives to develop an analytical estimation method of demand size that converts area based demand data to point based population weighted centroids. This method is free to spatial boundary units and more robust to estimate accurate demand volumes regardless of geographic boundaries. To improve the estimation accuracy, this paper uses house weighted value to the population centroid calculation process. Then the population weighted centroids are converted to individual demand points on a grid formated surface area. In turn, the population weighted centroids, demand points and network distance measures are operated into location-allocation models to examine their roles to enhance solution quality and applicability of GIS location models. Finally, this paper demonstrates the robustness of the weighted estimation method with the application of location-allocation models.

• Membrane and Water Treatment
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• v.9 no.6
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• pp.455-462
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• 2018

The measurement and monitoring of the biochemical oxygen demand (BOD) play an important role in the planning and operation of wastewater treatment plants. The most basic method for determining biochemical oxygen demand is direct measurement. However, this method is both expensive and takes a long time. A five-day period is required to determine the biochemical oxygen demand. This study has been carried out in a wastewater treatment plant in Turkey (Hurma WWTP) in order to estimate the biochemical oxygen demand a shorter time and with a lower cost. Estimation was performed using artificial neural network (ANN) method. There are three different methods in the training of artificial neural networks, respectively, multi-layered (ML-ANN), teaching learning based algorithm (TLBO-ANN) and artificial bee colony algorithm (ABC-ANN). The input flow (Q), wastewater temperature (t), pH, chemical oxygen demand (COD), suspended sediment (SS), total phosphorus (tP), total nitrogen (tN), and electrical conductivity of wastewater (EC) are used as the input parameters to estimate the BOD. The root mean squared error (RMSE) and the mean absolute error (MAE) values were used in evaluating performance criteria for each model. As a result of the general evaluation, the ML-ANN method provided the best estimation results both training and test series with 0.8924 and 0.8442 determination coefficient, respectively.

• 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.

• Journal of Korean Society of Transportation
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• v.19 no.1
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• pp.77-88
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• 2001

Until now, though most of the studies related to demand estimation method using traffic counts use methods based on singleclass, travel demands or flows are made by mixing various vehicles in real networks. In general, existing demand estimation methods based on traffic counts estimate O/D by converting a multiclass O/D matrix and traffic counts into a singleclass O/D matrix and traffic counts through PCE conversion, and analyze a O/D matrix by dividing into a multiclass O/D matrix and traffic counts after multiplying an estimated O/D matrix by the fixed ratio of a singleclass O/D matrix and traffic counts before PCE conversion. However, the merits of a demand estimation method based on multiclass calculate each route choice ratio about multiclass O/D, and maximize the estimation capability of multiclass by calculating each gradient, the reduction direction of objective function. Therefore, this study aims to establish a demand estimation method which considers congestion between vehicle and vehicle by using multiclass instead of singleclass.

• The Journal of Korean Medicine
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• v.19 no.1
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• pp.299-326
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• 1998

1. Comparison of demand and supply A. Assumption of estimation of demand and supply we will briefly assumptions used for presumption once more before comparing the result of estimation of demand and supply examined previously 1) supply - The average applying rate for state. examination of graduate: ${\alpha}$=1.03109 - The ratio of successful applicants of state examinations: ${\beta}$=0.97091 - Mortality classified by age : presumed data of the Bureau of statistics - Emigrating rate: 0 % - Time of retire: unconsidered - An army doctor number: unconsidered and regard number of employed oriental medicine doctor. - Standard of 1995 : The number of survival oriental medicine doctor is 8195. the number of employed oriental medicine doctor is 7419. 2) demand - derivated demand method Daily the average amount of medical treatment: according to medical insurance federation data. there is 16 or 6 non allowance patient, we consider amount of medical treatment as 22 persons in practical because 21.94 persons (founded practical examination) are converted to allowance in comming demand. Daily the proper amount of medical treatment: 7 hours form -35 persons 5 hours 30 minutes form -28 persons. Yearly medical treatment days: 229 days. 255 days. 269 days . Increasing rate of visiting hospital days: -1996 year. 1997 year. 1998 year- . Rate of applying insurance: yearly average 71.51% (among the investigated patient) B. Comparison of total sum result 1) supply (provision) Table Ⅳ-1 below shows the estimation of the oriental medicine doctor in the future.