• Journal of Digital Convergence
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• v.18 no.2
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• pp.205-211
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• 2020

The method of predicting the future may be predicted by technical characteristics or technical performance. Therefore, technology prediction is used in the field of strategic research that can produce economic and social benefits. In this study, we predicted the future market through the study of how to predict the future with these technical characteristics. The future prediction method was studied through the prediction of the time when the market occupied according to the demand of special product. For forecasting market demand, we proposed the future forecasting model through comparison of representative quantitative analysis methods such as CAGR model, BASS model, Logistic model and Gompertz Growth Curve. This study combines Rogers' theory of innovation diffusion to predict when products will spread to the market. As a result of the research, we developed a methodology to predict when a particular product will mature in the future market through the spread of various factors for the special product to occupy the market. However, there are limitations in reducing errors in expert judgment to predict the market.

• Journal of the Korea Organic Resources Recycling Association
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• v.21 no.2
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• pp.88-96
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• 2013

The objective of this research was to evaluate the suitability of sigmoidal and firstorder kinetic equations for simulating the methane production from solid wastes. The sigmoidal kinetic equations used were modified Gompertz and Logistic equations. Statistical criteria used to evaluate equation performance were analysis of goodness-of-fit (Residual sum of squares, Root mean squared error and Akaike's Information Criterion). Akaike's Information Criterion (AIC) was employed to compare goodness-of-fit of equations with same and different numbers of parameters. RSS and RMSE were decreased for first-order kinetic equation with lag-phase time, compared to the first-order kinetic equation without lag-phase time. However, first-order kinetic equations had relatively higher AIC than the sigmoidal kinetic equations. It seemed that the sigmoidal kinetic equations had better goodness-of-fit than the first-order kinetic equations in order to simulate the methane production.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.19 no.1
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• pp.35-40
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• 2014

Hatching date, main spawning period and growth of juvenile marbled flounder (Pseudopleuronectes yokohamae) were determined by analysis of microstructure in otoliths. Marbled flounders were collected by a small beam trawl in Namhae from February 2011 to January 2012. The length (L, mm) was related to body weight (W, g); $W=9.76^*10^{-8}L^{4.39}$ ($r^2=0.93$). The length was also related to otolith radius (R, ${\mu}m$); L=0.0795R+0.2249 ($r^2=0.92$). The growth in length was represented by Gompertz growth curve; $L_t=135{\exp}\{-{\exp}[0.0103(t-116)]\}$ ($r^2=0.83$). The hatching date calculated from the number of daily growth increments in otoliths was between mid-December and mid-February.

• Food Science and Biotechnology
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• v.16 no.2
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• pp.238-242
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• 2007

Square root models were developed for predicting the kinetics of growth of Listeria monocytogenes in sesame leaves as a function of temperature (4, 10, or $25^{\circ}C$). At these storage temperatures, the primary growth curves fit well ($R^2=0.898$ to 0.980) to a Gompertz equation to obtain lag time (LT) and specific growth rate (SGR). The square root models for natural logarithm transformations of the LT and SGR as a function of temperature were obtained by SAS's regression analysis. As storage temperature ($4-25^{\circ}C$) decreased, LT increased and SGR decreased, respectively. Square root models were identified as appropriate secondary models for LT and SGR on the basis of most statistical indices such as coefficient determination ($R^2=0.961$ for LT, 0.988 for SGR), mean square error (MSE=0.l97 for LT, 0.005 for SGR), and accuracy factor ($A_f=1.356$ for LT, 1.251 for SGR) although the model for LT was partially not appropriate as a secondary model due to the high value of bias factor ($B_f=1.572$). In general, our secondary model supported predictions of the effects of temperature on both LT and SGR for L. monocytogenes in sesame leaves.

• Journal of Korean Society of Forest Science
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• v.88 no.1
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• pp.47-54
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• 1999

To estimate optimal tree diameter and height growth function in Pinus thunbergii stands with site index of 12 class, quoted from two linear models of linear transformation(1) and linear transformation (2) and four non-linear models of exponential, Gompertz, Chapman-Richards, and Weibull etc.. Analyzed correlation among the estimated tree diameter and height by these function models, and observed diameter and height growth were compared. In the results of tree diameter and height growth estimation by stand age, non-linear models showed better appropriation than linear model and Chapman-Richards model was most fitted for tree height growth but few, if any, differences among their nonlinear models. Therefore, it is consider to be much more study about non-linear model to estimate tree diameter and height growth in the actual stands hereafter.

• Journal of the Korean Society of Food Science and Nutrition
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• v.42 no.5
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• pp.832-836
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• 2013

To develop a predictive model for the shelf-life of fish cake, fish cake was stored at 30, 35, or $40^{\circ}C$ and populations of total aerobic bacteria were determined during storage. Gompertz model parameters were determined and their dependence on temperature formulated as a quadratic equation for applications toward shelf-life prediction. The predicted shelf-life values for fish cake used in this study were 6.9, 5.5, and 3.8 days at 0, 4, and $10^{\circ}C$, respectively. The shelf-life prediction equation was appropriate based on statistical analyses that reveal accuracy and bias factors. These results suggest that our prediction model is applicable for estimating the shelf-life of fish cake.

• Environmental Engineering Research
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• v.24 no.1
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• pp.38-44
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• 2019

The Biochemical Methane Potential (BMP) of fresh leachate and domestic wastewaters codigestion was determined by laboratory Bach Tests at $35^{\circ}C$ over a period of 90 d using a wide range of leachates volumetric ratios from 0% to 100%. To simulate wastewaters plant treatment step, all the ratios were first air stripped for 48 h before anaerobic incubation. The kinetic of biogas production was assessed using modified Gompertz model and exponential equation. The results obtained showed that cumulative biogas production was insignificant in the case of wastewaters monodigestion while the codigestion significantly improves the BMP. Air stripping pretreatment had positive effect on both ammonium concentration and volatiles fatty acids with reduction up to 75% and 42%, respectively. According to the Modified Gompertz model, the optimal anaerobic co-digestion conditions both in terms of maximal biogas potential, start-up period and maximum daily biogas production rate, could be achieved within large leachate volumetric ratios from 25% to 75% with a maximum BMP value of 438.42 mL/g volatile solid at 50% leachate ratio. The positive effect of codigestion was attributed to a dilution effect of chemical oxygen demand and volatile fatty acid concentrations to optimal range that was between 11.7 to $32.3gO_2/L$ and 2.1 to 7.4 g/L, respectively. These results suggested that the treatment of fresh leachate by their dilution and co digestion at wastewaters treatment plants could be a promising alternative for both energetic and treatment purposes.

• 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.

• Management Science and Financial Engineering
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• v.14 no.2
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• pp.89-104
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• 2008

Growth curves including Bass, Logistic and Gompertz functions are widely used in forecasting the market demand. Nonlinear least square method is often adopted for estimating the model parameters but it is difficult to set up the starting value for each parameter. If a wrong starting point is selected, the result may lead to erroneous forecasts. This paper proposes a method of selecting starting values for model parameters in estimating some growth curves by nonlinear least square method through grid search and transformation into linear regression model. Resealing the market data using the national economic index makes it possible to figure out the range of parameters and to utilize the grid search method. Application to some real data is also included, where the performance of our method is demonstrated.

• Communications for Statistical Applications and Methods
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• v.21 no.1
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• pp.23-43
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• 2014

We study the dependence between the insureds in multiple-life insurance contracts. With the future lifetimes of the insureds modeled as correlated random variables, both premium and reserve are different from those under independence. In this paper, Gaussian copula is used to impose the dependence between the insureds with Gompertz marginals. We analyze the change of the reserves of standard multiple-life insurance contracts at various dependence levels. We find that the reserves based on the assumption of dependent lifetimes are quite different for some contracts from those under independence as its correlation increase, which elucidate the importance of the dependence model in multiple-life contingencies in both theory and practice.