• Journal of Biosystems Engineering
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• v.29 no.5 s.106
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• pp.441-450
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• 2004

This study was performed to estimate mid and long term demands of a tractor, a rice transplanter, a combine and a grain dryer by using logistic curve function and Markov chain model. Field survey was done to decide some parameters far logistic curve function and Markov chain model. Ceiling values of tractor and combine fer logistic curve function analysis were 209,280 and 85,607 respectively. Based on logistic curve function analysis, total number of tractors increased slightly during the period analysed. New demand for combine was found to be zero. Markov chain analysis was carried out with 2 scenarios. With the scenario 1(rice price $10\%$ down and current supporting policy by government), new demand for tractor was decreased gradually up to 700 unit in the year 2012. For combine, new demand was zero. Regardless of scenarios, the replacement demand was increased slightly after 2003. After then, the replacement demand is decreased after the certain time. Two analysis of logistic owe function and Markov chain model showed the similar trend in increase and decrease for total number of tractors and combines. However, the difference in numbers of tractors and combines between the results from 2 analysis got bigger as the time passed.

• Management Science and Financial Engineering
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• v.11 no.3
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• pp.125-136
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• 2005

As the importance of time-based competition is increasing, information systems for supporting the immediate decision making is strongly required. Especially high -tech product firms are under extreme pressure of rapid response to the demand side due to relatively short life cycle of the product. Therefore, the objective of our research is proposing a framework of estimating demand curve based on e-auction data, which is extremely easy to access and well reflect the limited demand curve in that channel. Firstly, we identify the advantages of using e-auction data for full demand curve estimation and then verify it using Agent-Eased-Modeling and Tobin's censored regression model.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.54 no.2
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• pp.79-87
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• 2005

At present Cournot model is one of the most commonly used theories to analyze the gaming situation in oligopoly market. But there exist several problems to apply this model to electricity market. The representative one is to obtain the inverse demand curve able to be induced from the relationship between market price and demand response. In Cournot model, each player offers their generation quantity to accomplish maximum profit, which is accomplished by reducing their quantity compared with available total capacity. As stated above, to obtain the probable Cournot equilibrium to reflect real market situation, we have to induce the correct demand function first of all. Usually the correlation between price and demand appears on the long-term basis through the statistical data analysis (for example, regression analysis) or by investigating consumer utility functions of several consumer groups classified as residential, industrial, and commercial. However, the elasticity has a tendency to change continuously according to the total market demand size or the level of market price. Therefore it should be updated as trading period passes by. In this paper we propose a method for inducing and updating this price elasticity of demand function for more realistic market equilibrium.

• KIEE International Transactions on Power Engineering
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• v.5A no.4
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• pp.403-411
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• 2005

At present, the Cournot model is one of the most commonly used theories to analyze the gaming situation in an oligopoly type market. However, several problems exist in the successful application of this model to the electricity market. The representative one is obtaining the inverse demand curve able to be induced from the relationship between market price and demand response. In the Cournot model, each player offers their generation quantity to obtain maximum profit, which is accomplished by reducing their quantity compared with available total capacity. As stated above, to obtain the probable Cournot equilibrium to reflect the real market situation, we have to induce the correct demand function first of all. Usually the correlation between price and demand appears over the long-term through statistical data analysis (for example, regression analysis) or by investigating consumer utility functions of several consumer groups classified as residential, industrial, and commercial. However, the elasticity has a tendency to change continuously according to the total market demand size or the level of market price. Therefore it should be updated as the trading period passes by. In this paper we propose a method for inducing and updating this price elasticity of demand function for more realistic market equilibrium.

• Journal of the Korean Operations Research and Management Science Society
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• v.10 no.1
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• pp.65-78
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• 1985

In this paper, the approach getting a total demand by forecasting the new demand and the replacement demand separately and adding them is used for long term forecasting of durable goods. Cross country analysis using the income as an independent variable and S-shaped growth curve as a fitting model is developed as a method of forecasting new demand. To get the replacement demand the methods using the number of ownership and the replacement rate and the methods using the past demand and the distribution of the product life are proposed. And the theoretical explannation for product life cycle's diversity, which is the one of the major considerations in the long term forecasting, is attempted by the combination of the new demand and the replacement demand patterns. This is applicated the long term forecasting of Korean passenger cars.

• 공원문화
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• s.26
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• pp.26-32
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• 1984

There have been few researches on the factors affecting forest recreation demand and demand for and value of forest recreation in Korea. This study has three main objectives as follows; First, to introduce the nature of recreation demand, the factors affecting forest recreation demand, and the methods of measuring demand for and benefits from forest recreation by reviewing related literatures. Secondly, to investigate the visitors' characteristics, patterns of recreation activities, and their attitudes for the recreation environments at the Deogyu National Park through interviewing them with the questionaire. Thirdly, to estimate the demand for and benefits of forest recreation at the National Park by Travel Cost Method. The survey was dealt by three trained interviewers at the enterance of the park for 5 days from September 26 to October 10, 1982. The 430 respondents were sampled randomly among 9,391 visitors with 4.6% of sampling rate. As the results, the study revealed that most of visitors to Deogyu National Park were from urban areas and belonged to the intermediate-upper income classes, and that most of them traveled more than 250 km or 4 hours to the site from their origins. And more respondents answered that the recreation environments of the cite were more or less better than other recreation areas. From the date of travel distances and participation rates of 13 cities or counties, the demand schedule of forest recreation at the National Park was established. The estimated equation of total experience demand curve is; Log $VR_i$ 2.6353 – 1.021 Log $D_i$ $R^2=0.9451$ where, $VR_i$ $(%\times1000)$ = Participation rate of the ith origin $D_i$ (km) = Travel distance from the ith origin From the total experience demand curve, the demand curve of recreation resources was built by adding travel cost in distance (km). The regression equation of the recreation resources at the Nation park is; Log V = 4.0304 – 0.8167 Log D $R^2=0.9060$ From the demand schedule of recreation resources, the recreational bendfits of Deogyu National Park was estimated. The estimated bendfits to a visitor from the forest is equivalent to the travel cost of 2,372 km. The study also found out that the demand for recreation resources was less elastic than the demand for the total recreation experience at the Deogyu National Park.

• Journal of Korean Society for Quality Management
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• v.50 no.3
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• pp.349-371
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• 2022

Purpose: Compared to the rapid growth rate of the domestic automotive LED industry so far, the predictive analysis method for demand forecasting or market outlook was insufficient. Accordingly, product characteristics are analyzed through the life trend of LEDs for automotive exterior lamps and the relative strengths of p and q using the Bass model. Also, future demands are predicted. Methods: We used sales data of a leading company in domestic market of automotive LEDs. Considering the autocorrelation error term of this data, parameters m, p, and q were estimated through the modified estimation method of OLS and the NLS(Nonlinear Least Squares) method, and the optimal method was selected by comparing prediction error performance such as RMSE. Future annual demands and cumulative demands were predicted through the growth curve obtained from Bass-NLS model. In addition, various nonlinear growth curve models were applied to the data to compare the Bass-NLS model with potential market demand, and an optimal model was derived. Results: From the analysis, the parameter estimation results by Bass-NLS obtained m=1338.13, p=0.0026, q=0.3003. If the current trend continues, domestic automotive LED market is predicted to reach its maximum peak in 2021 and the maximum demand is $102.23M. Potential market demand was $1338.13M. In the nonlinear growth curve model analysis, the Gompertz model was selected as the optimal model, and the potential market size was $2864.018M. Conclusion: It is expected that the Bass-NLS method will be applied to LED sales data for automotive to find out the characteristics of the relative strength of q/p of products and to be used to predict current demand and future cumulative demand.

• Journal of the Earthquake Engineering Society of Korea
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• v.15 no.6
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• pp.33-44
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• 2011

The shape of an inelastic demand spectrum may have a major impact on the seismic evaluation results of a structure. The inelastic demand spectrum could be obtained by scaling down from the elastic response spectrum by applying the strength reduction factor (SRF). This study has investigated formulas for SRFs that were suggested by numerous previous studies. This paper compares their characteristics, including the shapes of the curves of the SRFs and the inelastic demand spectra that were produced by applying the various formulas for SRFs. The mean curve was computed from the SRF curves generated by the various formulas. This study derives a new formula for the SRF curve through regression analysis. From the comparative study, it is shown that the proposed formula for the SRF can generate the mean curve of the inelastic demand spectra which have been previously suggested by others.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.4
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• pp.534-541
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• 2012

This paper tries to elicit an optimal generation mix of Korea. Two approaches, using the screening curve method and taking advantage of a generation expansion planning tool, WASP-IV, are applied in getting the mix. The data used in this study is based on the 5th basic plan for long-term electricity supply and demand. The Load Duration Curve, that is needed for applying Screening Curve Method(SCM), is made based on the load profile in 2010. In our using SCM, the nuclear plant's operation characteristic, carbon emission cost and spinning reserve are considered. In using WASP-IV to get the adequate generation mix, the base and target demand forecasts in the 5th basic plan are used and the carbon emission cost is also considered. In this paper, It introduces the domestic adequacy generation mix in 2024 though SCM and WASP-IV.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.53 no.3
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• pp.182-186
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• 2004

In this paper, the cost for capacitive reactive flower is evaluated considering the deregulation environment. For the cost assessment of reactive power, the duration curve of reactive power demand is introduced and investigated. Also, a guideline is suggested to estimate the Q-cost by using the inverse of the Q-demand duration curve. In order to obtain optimal real reactive power allocation, a new algorithm is proposed by using the piecewise linearization of the inverse of the Q-demand duration curve and the Linear Programming technique. The proposed method is tested with sample systems using MATLAB. The test results show that the algorithm yields reasonable reactive power allocation and Provides fair cost evaluation for reactive power.