• Journal of the Korean Operations Research and Management Science Society
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• v.16 no.1
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• pp.120-134
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• 1991

Various technological forecasting models have been proposed to represent the time pattern of technological growths. Of six such models studied, some models do significantly better than others, especially at low penetration levels, in predicting future levels of growth. Criteria for selecting an appropriate model for technological growth model are examined in this study. Two major characteristics were selected which differentiate the various models ; the skew of the curve and the underlying assumptions regarding the variance of the error structure of the model. Although the use of statistical techniques stil requires some subjective input and interpretations, this study provides some practical procedures in the selection of technological growth models and helps to reduce or control the potential source of judgmental error inconsistencies in the analyst's decision.

• Journal of the Korean Institute of Landscape Architecture
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• v.39 no.6
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• pp.110-117
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• 2011

In order to study the growth models between the growth of Sedum takevimense and growth rate in soil with three types of mix ratios, this experiment was carried out on April 3rd, 2011. A nonlinearity regression analysis was performed using the Logistic and Gompertz models by SPSS. According to the study of growth models of Sedum takevimense, the process of growth and management methods after over-wintering were explicitly determined. According to the measured values, the growth in the soil of $P_1P_2V_1$ and $P_2P_1V_1$ was better than that of $P_1$. Particularly, the average length of Sedum takevimense in the soil of $P_1P_2V_1$ was about twice as great as that in the $P_1$. The fitness test of the two growth models was: The predicted value and measured value were separately compared and analysed, the average fitting precision $R^2$ of the Logistic models was 0.995, but the average $R^2$ of the Gompertz models was below 0.978, which showed that the Logistic models were better than the Gompertz models. The growth models also showed that the growth time of Sedum takevimense was divided into three: rapid, most rapid and slow. When managed in the rapid and the most rapid time, it will grow better.

• Journal of Forest and Environmental Science
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• v.24 no.3
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• pp.119-126
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• 2008

Growth and yield prediction methods, ranging from whole-stand models to individual-tree models, have been developed for forest types managed for wood production. The resultant models are used for a host of purposes including inventory updating, management planning, evaluation of silvicultural alternatives, and harvest scheduling. Because of the large investment in developing growth and yield models for improved genotypes and silvicultural practices for loblolly pine (Pinus taeda) in the Southern United States, this region serves to illustrate approaches for modelling intensively managed forests. Analytical methods and computing power generally do not restrict development of reliable growth and yield models. However, long-term empirical observations on stand development, which are time consuming and expensive to obtain, often limit modelling efforts. Given that growth and yield models are used to project present volumes and to evaluate alternative treatment effects, data of both the inventory type and the experimental type are needed. Data for developing stand simulators for loblolly pine plantations have been obtained from a combination of permanent plots in operational forest stands and silvicultural experiments; these data collection efforts are described and summarized. Modelling is essential for integrating and synthesizing diverse information, identifying knowledge gaps, and making informed decisions. The questions being posed today are more complex than in the past, thus further accentuating the need for comprehensive models for stand development.

• ETRI Journal
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• v.36 no.3
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• pp.450-459
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• 2014

In this paper, we present a new, easy-to-generate system that is capable of creating virtual 3D tree models and simulating a variety of growth processes of a tree from a single, real tree image. We not only construct various tree models with the same trunk through our proposed digital image matting method and skeleton-based abstraction of branches, but we also animate the visual growth of the constructed 3D tree model through usage of the branch age information combined with a scaling factor. To control the simulation of a tree growth process, we consider tree-growing attributes, such as branching orders, branch width, tree size, and branch self-bending effect, at the same time. Other invisible branches and leaves are automatically attached to the tree by employing parametric branch libraries under the conventional procedural assumption of structure having a local self-similarity. Simulations with a real image confirm that our system makes it possible to achieve realistic tree models and growth processes with ease.

• Asian-Australasian Journal of Animal Sciences
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• v.12 no.2
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• pp.282-286
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• 1999

Growth of pigs is influenced by many factors. To assist pig producers in the evaluation of alternative feeding and management strategies growth models have been developed. In the Netherlands the Technical Model Pigfeeding (TMV) is developed. This model predicts the influence of feed intake, feed composition, genotype, sex and climate on growth, body composition, gross margin and mineral excretion of healthy growing/finishing pigs. The purpose of TMV is to support information services, feed companies, researchers and students. In addition to providing accurate predictions, a model should also be user-friendly and wishes of the user should be taken into account to stimulate application of the model in practice. In this paper, the theoretical background of TMV and a methodology to stimulate application of models in practice will be described.

• Journal of Applied Reliability
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• v.13 no.3
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• pp.217-227
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• 2013

Reliability growth is defined as the positive improvement in a reliability parameter over a period of time due to implementation of corrective actions to system design, operation or maintenance procedures, or the associated manufacturing process. In recent, the importance of reliability growth management has emerged in the military authority and industries. For effective application of reliability growth models, it is necessary to understand their characteristics and differences. This paper presents the concepts of reliability growth management and compares the features of reliability tracking and projection models centered on MIL-HDBK-189C for selecting the appropriate model for an one-shot system under development.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.32 no.4
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• pp.184-191
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• 2009

In a technological driven environment, a depreciation estimate which is based on traditional life analysis results in a decelerated rate of capital recovery. This time pattern of technological growths models needs to be incorporated into life analysis framework especially in those industries experiencing fast technological changes. The approximation technique for calculating the variance can be applied to the six growth models that were selected by the degree of skewness and the transformation of the functions. For the Pearl growth model, the Gompertz growth model, and the Weibull growth model, the errors have zero mean and a constant variance over time. However, transformed models like the linearized Fisher-Pry model, the linearized Gompertz growth model, and the linearized Weibull growth model have increasing variance from zero to that point at which inflection occurs. It can be recommended that if the variance of error over time is increasing, then a transformation of observed data is appropriate.

• Journal of Forest and Environmental Science
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• v.31 no.4
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• pp.255-260
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• 2015

Height growth models for Pinus thunbergii in Jeju Island were developed in this study using four widely used nonlinear growth models; Exponential, Modified Logistic, Chapman-Richards, and Weibull. All functions were found to be significant at the 1% level. Chapman-Richards model for height-DBH allometry and Weibull model for height-age allometry was chosen as the best model on the all validation. All the model curves showed the similar pattern. Additionally, there was no abnormal pattern when the previous studies were compared. Therefore, these models are highly expected to be used to estimate the tree height using DBH or age for Pinus thunbergii especially in Jeju Island.

• Korean Journal of Organic Agriculture
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• v.25 no.2
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• pp.279-293
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• 2017

This study suggests the yield forecast models for autumn chinese cabbage and radish using crop growth and development information. For this, we construct 24 alternative yield forecast models and compare the predictive power using root mean square percentage errors. The results shows that the predictive power of model including crop growth and development informations is better than model which does not include those informations. But the forecast errors of best forecast models exceeds 5%. Thus it is important to establish reliable data and improve forecast models.

• 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.