• Title/Summary/Keyword: Nonlinear Growth Curve Model

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Domestic Automotive Exterior Lamp-LEDs Demand and Forecasting using BASS Diffusion Model (BASS 확산 모형을 이용한 국내 자동차 외장 램프 LED 수요예측 분석)

  • Lee, Jae-Heun
    • 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.

A Study on the Analysis Procedures of Nonlinear Growth Curve Models (비선형 성장곡선 모형의 분석 절차에 대한 연구)

  • 황정연
    • Journal of Korean Society for Quality Management
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    • v.25 no.1
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    • pp.44-55
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    • 1997
  • In order to determine procedures for a, pp.opriate model selection of technological growth curves, numerous time series that were representative of growth behavior were collected according to data characteristics. Three different growth curve models were fitted onto data sets in an attempt to determine which growth curve models achieved the best forecasts for types of growth data. The analysis of the results gives rise to an a, pp.oach for selecting a, pp.opriate growth curve models for a given set of data, prior to fitting the models, based on the characteristics of the goodness of fit test.

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Application of Bootstrap Method to Primary Model of Microbial Food Quality Change

  • Lee, Dong-Sun;Park, Jin-Pyo
    • Food Science and Biotechnology
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    • v.17 no.6
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    • pp.1352-1356
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    • 2008
  • Bootstrap method, a computer-intensive statistical technique to estimate the distribution of a statistic was applied to deal with uncertainty and variability of the experimental data in stochastic prediction modeling of microbial growth on a chill-stored food. Three different bootstrapping methods for the curve-fitting to the microbial count data were compared in determining the parameters of Baranyi and Roberts growth model: nonlinear regression to static version function with resampling residuals onto all the experimental microbial count data; static version regression onto mean counts at sampling times; dynamic version fitting of differential equations onto the bootstrapped mean counts. All the methods outputted almost same mean values of the parameters with difference in their distribution. Parameter search according to the dynamic form of differential equations resulted in the largest distribution of the model parameters but produced the confidence interval of the predicted microbial count close to those of nonlinear regression of static equation.

Derivation of Profit Curve by Cubic Cost Function and Mathematical Verification of Industry Life Cycle: Focused on All Industries in Korea (3차 비용함수에 의한 이익곡선 도출과 산업 라이프사이클의 수리적 검증: 우리나라 전 산업을 중심으로)

  • Hoo Seok Pai;Chae Kwan Lim
    • Journal of Korean Society for Quality Management
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    • v.51 no.4
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    • pp.481-496
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    • 2023
  • Purpose: The main theme of this study is to derive a profit curve by a cubic cost function for nonlinear CVP analysis. According to the analytical approach to derive a nonlinear profit function in this study, it is possible with only the existing cost structure to calculate the profit maximization and downtime point sales unlike the classical CVP analysis. Furthermore, the profit curve by the mathematical model of this study could serve as a tool to quantify the qualitative evaluation of each stage of the industry life cycle. Methods: This study followed the mathematical approach from the cubic cost function model of microeconomics, and using real data of the Bank of Korea Results: The nonlinear profit function suggested by this study is as follows; ${\pi}(x)=-a\left(x-\frac{f}{1-v}\right)^3+(1-v)x-k$ where $a=\frac{1}{3}v\left(\frac{(1-v)}{f}\right)^2,k=f-a\left(1-\frac{f}{1-v \right)^3$ Conclusion: The process and results of this study would be able to contribute not only in practice of nonlinear CVP analysis required in the management accounting or financial management, but also in cost theory of microeconomics. Also, since the life cycle of all industries in Korea was verified to the growth or mature stage, decision makers should pay careful attention to determining life cycle stages and consider the profit curve by the average variable cost ratio over multi periods.

Models Describing Growth Characteristics of Holstein Dairy Cows Raised in Korea

  • Vijayakumar, Mayakrishnan;Choy, Yun-Ho;Kim, Tae-Il;Lim, Dong-Hyun;Park, Seong-Min;Alam, Mahboob;Choi, Hee-Chul;Ki, Kwang-Seok;Lee, Hyun-Jeong
    • Journal of The Korean Society of Grassland and Forage Science
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    • v.40 no.3
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    • pp.167-176
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    • 2020
  • The objective of the present study was to determine the best model to describe and quantify the changes in live body weight, height at withers, height at rump, body length and chest girth of Holstein cows raised under Korean feeding conditions for 50 months. The five standard growth models namely polynomial linear regression models, regression of growth variables on the first and second-order of ages in days (model 1) and regression of growth variables on age covariates from first to the third-order (model 2) as well as non-linear models were fitted and evaluated for representing growth pattern of Holstein cows raised in Korean feeding circumstances. Nonlinear models fitted were three exponential growth curve models; Brody, Gompertz, and von Bertalanffy functional models. For this purpose, a total of 22 Holstein cows raised in Korea used in the period from April 2016 to May 2020. Each model fitted to monthly growth curve records of dairy cows by using PROC NLIN procedure in SAS program. On the basis of the results, nonlinear models showed the lower root mean square of error (RMSE) for live body weight, height at withers, height at rump, body length and chest girth (12.22, 1.95, 1.55, 4.04, 2.06) with higher correlation coefficiency (R2) values for live body weight, height at withers, height at rump, body length and chest girth (0.99, 0.99, 0.99, 1.00, 1.00). Overall, the evaluation of the different growth models indicated that the Gompertz model used in the study seemed to be the most appropriate one for standard growth of Holstein cows raised under Korean feeding system.

Development of fertilizer-distributed algorithms based on crop growth models (작물생육모형 기반 비료시비량 분배 알고리즘 개발)

  • Doyun Kim;Yejin Lee;Tae-Young Heo
    • The Korean Journal of Applied Statistics
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    • v.36 no.6
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    • pp.619-629
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    • 2023
  • Fertilizers are crucial for increasing crop yield, but using too much of them without taking into account the nutrients that the crops need can increase costs for farm management and have a negative impact on the environment. Through smart agriculture, fertilizers can be applied as needed at the right time to reflect the growth characteristics of crops, reducing the burden of fertilizer losses and providing economical nutrient management. In this study, we use the total dry weight of field-cultivated red pepper and green onion grown in various growing environments to fit a nonlinear model-based crop growth model using different growth curves (logistic, Gompertz, Richards, and double logistic curve), and we propose a fertilizer distributed algorithm based on crop growth rate.

Characteristics of Individual Growth Curve by Porcine LEPR-derived Microsatellite Polymorphisms (돼지의 Leptin receptor 유전자내 초위성체 다형성에 따른 개체별 성장곡선 특성)

  • Cho, Y.M.;Choi, B.H.;Kim, T.H.;Lee, J.W.;Cheong, I.C.
    • Journal of Animal Science and Technology
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    • v.45 no.6
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    • pp.885-890
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    • 2003
  • This study was conducted to estimate the growth curve parameters of 253 heads of F2 population produced by inter-crossing F1 from Korean Native boars and Landrace sows, and to estimate the effects of Leptin receptor gene(LEPR) on their growth characteristics. Growth curve parameters were estimated from nonlinear regression using Gompertz model individually. Average mature weight and average maturing rate estimated were 179.69${\pm}$4.40kg and 0.3103${\pm}$0.0043, respectively. The effect of sex was insignificant for all the parameters estimated from Gempertz model(p〉.05), and the effect of calving group was significant for mature weight and maximum growth rate at inflection point (p〈.05). The effect of LEPR genotype were significant for all the growth curve parameters(p〈.05). According from the results of the least squares means of growth curve parameters by LEPR genotypes, mature weight and point of inflection were highest in genotype AA in which the maturing rate was the lowest, and were lowest in genotype DD in which maturing rate was the highest, reversely.

A Comparison of Technological Growth Models

  • Oh, Hyun-Seung;Moon, Gee-Ju
    • Journal of Korean Society for Quality Management
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    • v.22 no.2
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    • pp.51-68
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    • 1994
  • Various growth models were each fitted onto the data sets in an attempt to determine which growth models achieved the best forecasts for differing types of growth data. Of six such models studied, some models do significantly better than others in predicting future levels of growth. It is recommened that Weibull and the Gompertz growth curve be considered along with Pearl model by those industries presently considering the implementation of substitution analysis in their life analysis. In the early stage of growth, linear estimation should suffice to give reasonable forecasts. In the latter stage, however, as more data become availavle, nonlinear estimation should be used.

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Growth curve estimates for wither height, hip height, and body length of Hanwoo steers (Bos taurus coreanae)

  • Park, Hu-Rak;Eum, Seung-Hoon;Roh, Seung-Hee;Sun, Du-Won;Seo, Jakyeom;Cho, Seong-Keun;Lee, Jung-Gyu;Kim, Byeong-Woo
    • Korean Journal of Agricultural Science
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    • v.44 no.3
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    • pp.384-391
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    • 2017
  • Growth curves in Hanwoo steers were estimated by Gompertz, Von Bertalanffy, Logistic, and Brody nonlinear models using growth data collected by the Hanwoo Improvement Center from a total of 6,973 Hanwoo (Bos taurus coreanae) steers 6 to 24 months old that were born between 1996 and 2015. The data included three parameters: A, mature size of body measurement; b, growth ratio; and, k, intrinsic growth rate. Nonlinear regression equations for wither height according to Gompertz, Von Bertalanffy, Logistic, and Brody models were $Y_t=144.7e^{-0.5869e^{-0.00301t}}$, $Y_t=145.3(1-0.1816e^{-0.00284t})^3$, $Y_t=143.1(1+0.7356e^{-0.00352t})^{-1}$, and $Y_t=146.8(1+0.4700e^{-0.00249t})^1$, respectively, while those for hip height were $Y_t=144.5e^{-0.5549e^{-0.00312t}}$, $Y_t=145.0(1-0.1724e^{-0.00295t})^3$, $Y_t=143.1(1+0.6863e^{-0.00360t})^{-1}$, and $Y_t=146.2(1+0.4501e^{-0.00263t})^1$, respectively. Equations for body length $Y_t=174.1e^{-0.8342e^{-0.00289t}}$, $Y_t=175.8(1-0.2500e^{-0.00265t})^3$, $Y_t=170.0(1+1.1548e^{-0.00363t})^{-1}$, and $Y_t=180.3(1+0.6077e^{-0.00215t})^1$, respectively, for the same models. Among the four models, the Brody model resulted in the lowest mean square error, with mean square errors of 31.79, 30.57, and 42.13, respectively, for wither height, hip height, and body length. Also, an estimated birth wither height, birth hip height, and birth body length (77.98, 80.57, and 70.97 cm, respectively) were lower in the Brody model than in other models. An inflection point was not observed during the growth phase of Hanwoo steer according to the growth curves calculated using Gompertz, Von Bertalanffy, and Logistic models. Based on the results, we concluded that the regression equation using the Brody model was the most appropriate among the four growth models. To obtain more accurate parameters, however, using data from a wider production period (from birth to shipping) would be required, and the development of a suitable model for body conformation traits would be needed.

Re-estimation of Model Parameters in Growth Curves When Adjusting Market Potential and Time of Maximum Sales (성장곡선 예측 모형의 특성치 보정에 따른 매개변수의 재추정)

  • Park, Ju-Seok;Ko, Young-Hyun;Jun, Chi-Hyuck;Lee, Jae-Hwan;Hong, Seung-Pyo;Moon, Hyung-Don
    • IE interfaces
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    • v.16 no.1
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    • pp.103-110
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    • 2003
  • Growth curves are widely used in forecasting the market demand. When there are only a few data points available, the estimated model parameters have a low confidence. In this case, if some expert opinions are available, it would be better for predicting future demand to adjust the model parameters using these information. This paper proposes the methodology for re-estimation of model parameters in growth curves when adjusting market potential and/or time of maximum sales. We also provide the detailed procedures for five growth curves including Bass, Logistic, Gompertz, Weibull and Cumulative Lognormal models. Applications to real data are also included.