• The KIPS Transactions:PartD
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• v.11D no.7 s.96
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• pp.1451-1458
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• 2004

Current software reliability growth models based on Gompertz growth curve are all logarithmic type. Software reliability growth models based on logarithmic type Gompertz growth curve has difficulties in parameter estimation. Therefore this paper proposes a software reliability growth model based on the logistic type Gompertz growth curie. Its usefulness is empirically verified by analyzing the failure data sets obtained from 13 different software projects. The parameters of model are estimated by linear regression through variable transformation or Virene's method. The proposed model is compared with respect to the average relative prediction error criterion. Experimental results show that the pro-posed model performs better the models based on the logarithmic type Gompertz growth curve.

• Journal of the Korea Society of Computer and Information
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• v.19 no.12
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• pp.219-225
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• 2014

A Gompertz modeling, sigmoid in shape, is a widely used application for social science, natural science, engineering, and medical research to allow confident approximation and accurate analysis and has been applied to estimate an elderly population on aging of population. Due to the high toxicity of currently available drug delivery vehicles, various efforts have been made to reduce side-effects in clinical fields, but its application to preclinical and clinical studies is limited and there are some difficulties to optimize the parameters of Gompertz modeling applicable to preclinical studies. Therefore, in this study, we demonstrated the ability of sickle red blood cells loaded by hypotonic dialysis then photosensitized and light-activated ex vivo for controlled release and simultaneously optimized Gompertz function to evaluate controlled drug release properties of photosensitized sickle red blood cells to reduce pain-related treatments in cancer patients.

• Journal of Korea Society of Digital Industry and Information Management
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• v.10 no.2
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• pp.29-36
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• 2014

Finite failure NHPP software reliability models presented in the literature exhibit either constant, monotonic increasing or monotonic decreasing failure occurrence rates per fault. In this paper, proposes the Gompertz distribution reliability model, which made out efficiency application for software reliability. Algorithm to estimate the parameters used to maximum likelihood estimator and bisection method, model selection based on mean square error (MSE) and coefficient of determination$(R^2)$, for the sake of efficient model, was employed. Analysis of failure using real data set for the sake of proposing fixed shape parameter of the Gompertz distribution was employed. This analysis of failure data compared with the Gompertz distribution model of shape parameter. In order to insurance for the reliability of data, Laplace trend test was employed. In this study, the proposed Gompertz model is more efficient in terms of reliability in this area. Thus, Gompertz model can also be used as an alternative model. From this paper, software developers have to consider the growth model by prior knowledge of the software to identify failure modes which can was helped.

• The KIPS Transactions:PartD
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• v.15D no.2
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• pp.207-212
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• 2008

This paper evaluates software cost estimation models, and presents the most suitable model. First, we transformed a relevant model into variables to make in linear. Second, we evaluated model's performance considering how much suitable the cost data of the actual development software was. In the stage of model performance evaluation criteria, we used MMRE which is the relative error concept rather than the absolute error. Existing software cost estimation model follows Weibull, Gamma, and Rayleigh function. In this paper, Gompertz function model is suggested which is a kind of growth curve. Additionally, we verify the compatability of other different growth curves. As a result of evaluation of model's performance, Gompertz function was considered to be the most suitable for the cost estimation model.

• Journal of the Korean Data and Information Science Society
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• v.10 no.2
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• pp.445-455
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• 1999

We modify the Gompertz regression model for estimation of cure rates from pediatric clinical trials by assuming different hazard rates on the different periods. A treatment period may be divided by the stages of treatments under the different treatment arms. The piecewise Gompertz models provide an efficient method for estimation of the cure rates and a method for testing the difference of the treatment effects in the given interval.

• Journal of applied mathematics & informatics
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• v.18 no.1_2
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• pp.311-320
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• 2005

Studies in the evolutionary biology of aging require good estimates of the age-dependent mortality rate coefficient (one of the Gompertz parameters). In this paper we introduce an alternative algorithm for estimating this parameter. And we discuss the sensitivity of the estimates to changes in the other model parameters.

• Asian-Australasian Journal of Animal Sciences
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• v.11 no.1
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• pp.84-88
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• 1998

The aim of this study was to describe growth patterns of mice using Gompertz model. Two distinct types of mice, laboratory mouse $CF_{\sharp1}$ (Mus musculus domesticus) and Yonakuni wild mouse (Yk, Mus musculus molossinus yonakuni) were used. From all possible crosses, there were two parental types and two reciprocal $F_1$ crosses obtained. Individual body weights were measured weekly from birth to ten weeks of age on 321 mice. Standardization to six mice was conducted and only first litters were used. Growth curve parameters were estimated to fit growth data. The results showed that growth among genetic groups were significantly different (p < 0.05) for both sexes, in which parental type of $CF_{\sharp1}$ and Yk had the highest and the smallest values, respectively. Meanwhile, reciprocal $F_1$ crosses were intermediate between parental types. It was concluded that Gompertz model provided and excellent fit for the growth data with a high coefficient determination $(R^2 = 0.999)$.

• Asian-Australasian Journal of Animal Sciences
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• v.12 no.8
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• pp.1177-1180
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• 1999

This study describes the growth of broiler chickens to the two forms of Gompertz function for application in broiler production models. The first form is based on the estimated mature weight ($W_A$), while the second is based on the estimated hatch weight ($W_O$). Both equations gave identical estimation because they are mathematically identical. To fit the growth curve of commercial broilers that marketed at 35-42 days, it is unnecessary to keep broilers to near maturity (> day 140) to obtain growth data for deriving the Gompertz function. This date does not improve the curve fitting of the early growing period. Additionally, a high mortality and health problem occurred to this type of chicken after day 105.

• Communications for Statistical Applications and Methods
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• v.21 no.6
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• pp.521-528
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• 2014

A stochastic Gompertz diffusion model for tumor growth is a topic of active interest as cancer is a leading cause of death in Korea. The direct maximum likelihood estimation of stochastic differential equations would be possible based on the continuous path likelihood on condition that a continuous sample path of the process is recorded over the interval. This likelihood is useful in providing a basis for the so-called continuous record or infill likelihood function and infill asymptotic. In practice, we do not have fully continuous data except a few special cases. As a result, the exact ML method is not applicable. In this paper we proposed a method of parameter estimation of stochastic Gompertz differential equation via Markov chain Monte Carlo methods that is applicable for several data structures. We compared a Markov transition data structure with a data structure that have an initial point.

• Journal of the Korean Solar Energy Society
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• v.39 no.6
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• pp.113-125
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• 2019

With the opening of the small power brokerage business market in December 2018, the small power trading market has started in Korea. Operators must submit the day-ahead estimates of power output and receive incentives based on its accuracy. Therefore, the accuracy of power generation forecasts is directly affects profits of the operators. The forecasting process for power generation can be divided into two procedure. The first is to forecast solar irradiation and the second is to transform forecasted solar irradiation into power generation. There are two methods for transformation. One is to simulate with physical model, and another is to use regression model. In this study, we found the best-fit regression model by analyzing hourly data of PV output and solar irradiation data during three years for 242 PV plants in Korea. The best model was not a linear model, but a sigmoidal model and specifically a Gompertz model. The combined linear regression and Gompertz curve was proposed because a the curve has non-zero y-intercept. As the result, R² and RMSE between observed data and the curve was significantly reduced.