• The Journal of Fisheries Business Administration
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• v.46 no.3
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• pp.103-118
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• 2015

The purpose of this paper is to discuss possibilities of applying growth curve models, such as Logistic, Log-Logistic, Log-Normal, Gompertz and Weibull, to three specific technology areas of Fishery Science and Technology in the process of measuring their technology level between Korea and countries with the state-of-the art level. Technology areas of hazard control of organism, environment restoration, and fish cluster detect were selected for this study. Expert panel survey was conducted to construct relevant panel data for years of 2013, 2016, and a future time of approaching the theoretical maximum technology level. The size of data was 70, 70 and 40 respectively. First finding is that estimation of shape and location parameters of each model was statistically significant, and lack-of-fit test using estimated parameters was statistically rejected for each model, meaning all models were good enough to apply for measuring technology levels. Second, three models other than Pearl and Gompertz seemed very appropriate to apply despite the fact that previous case studies have used only Gompertz and Pearl. This study suggests that Weibull model would be a very valid candidate for the purpose. Third, fish cluster detect technology level is relatively higher for both Korea and a country with the state-of-the-art among three areas as of 2013. However, all three areas seem to be approaching their limits(highest technology level point) until 2020 for countries with the state-of-the-art. This implies that Korea might have to speed up her research activities in order to catch up them prior to 2020. Final suggestion is that future study may better apply various and more appropriate models respectively considering each technology characteristics and other factors.

• Korean Journal Plant Pathology
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• v.14 no.4
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• pp.331-338
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• 1998

To develop the model for prediction of potato late blight progress, the relationship between severity index of potato late blight transformed by the logit and Gompit transformation function and cumulative severity value (CSV) processing weather data during growing period in Taegwallyeong alpine area, 1975 to 1992 were examined. When logistic model and Gompertz model were compared by determining goodness of fit for progressive degree of late blight using CSV as independent variable, the coefficients of determination were higher as 0.742 in the logistic model than 0.680 in the Gompertz model. Parameters in logistic model were composed of progressive rate and initial value of logistic model. Initial value was calculated in -3.664. The progressive rate of potato late blight was 0.137 in cv. Superior, 0.136 in cv. Irish Cobbler, and 0.070 in cv. Jopung without fungicide sprays. According to in crease of the number of spray times the progressive rate was lowered, was 0.020 in cv. Superior under the conventional program of fungicide sprays, 10 times sprays during cropping season. Equation of progressive rate, b1=0.0088 ACSV-0.033 (R2=0.976), was written by examining the relationship between the parameters of progressive rate of late blight and the average CSV (ACSV) quantifing weather information. By estimating parameters of logistic function, model able to describe the late blight progress of potato, cv. Superior was formulated in Y=4/(1+39.0·exp((0.0088 ACSV-0.033)·CSV).

• 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.

• Korean Journal Plant Pathology
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• v.14 no.2
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• pp.150-156
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• 1998

To develop a model for prediction of turnip mosaic virus(TuMV) disease progress of Chinese cabbage based on weather information and number of TuMV vector aphids trapped in Taegwallyeong alpine area, data were statistically processed together. As the variables influenced on TuMV disease progress, cumulative portion(CPT) above 13$^{\circ}C$ in daily average temperature was the most significant, and solar radiation, duration of sunshine, vector aphids and cumulative temperature above $0^{\circ}C$ were significant. When logistic model and Gompertz model were compared by detemining goodness of fit for TuMV disease progress using CPT as independent variable, regression coefficient was higher in the logistic model than in the Gompertz model. Epidemic parameters, apparent infection rate and initial value of logistic model, were estimated by examining the relationship between disease proportion linearized by logit transformation equation, In(Y/Yf-Y) and CPT. Models able to describe the progression of TuMV disease were formulated in Y=100/(1+128.4 exp(-0.013.CPT.(-1(1/(1+66.7.exp(-0.11.day). Calculated disease progress from the model was in good agreement with investigated actual disease progress showing high significance of the coefficient of determination with 0.710.

• Korean Journal of Poultry Science
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• v.49 no.4
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• pp.229-237
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• 2022

This study investigated the growth characteristics of four strains of newly developed synthetic Korean native commercial chickens (KNCs). We investigated a suitable growth curve model in KNCs and estimated the number of days to reach a 2 kg market weight. Body weight was measured at 2-week intervals from birth to 12 weeks of age. The growth curves were estimated using von Berteralanffy, Gompertz, and logistic functions. The results showed that males were significantly heavier than females at all ages, but there were no significant differences in body weight between strains, except at birth and 2 and 6 weeks of age. The coefficients of determination and adjusted determination of growth function had high goodness-of-fit (97.4~99.7). Of the growth curve parameters, the mature weight and growth ratio were higher in males than in females, but the maturity rate was similar in males and females. The inflection point occurred at approximately 7 weeks of age for females and 8 to 9 weeks of age for males. The weights estimated from the growth curve functions almost agreed with the actual weights, except for male weights estimated using the von Bertalanffy function. The coefficients of determination of the regression equations for weight to age were 0.9583 to 0.9746. The 8- and 10-week-old body weights estimated using the regression equation, and the 12-week-old weight estimated using the logistic function were most similar to the actual weight. Using these models, the estimated age of KNCs to reach 2 kg was 62.0~64.6 days for males and 74.9~78.6 days for females.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.76-76
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• 2022

과거 2015년 파리협정 채택을 기점으로 전 세계는 산업화 이전 대비 지구 평균온도 상승폭을 1.5℃ 이하로 억제하기 위한 노력을 지속적으로 강조하였다. 기후변화 완화를 위한 가장 적극적인 해결책으로 탄소중립 사회 전환이 제시되고 있으며, 이를 실행하기 위해서는 각 부문별 구체화된 탄소중립 추진 계획 수립이 요구된다. 특히 국내에서는 기후기술 분야에 특화된 기술수준 정보가 부족하여 국가 정책 수립에 어려움이 있다. 기술개발을 위한 정책 수립 시에는 기후기술의 정량적인 수준을 고려한 정책 방향을 결정해야 하지만, 국내에는 기술에 대한 분석에 대한 사례가 미흡한 실정이다. 본 연구에서는 수자원 분야의 국가경쟁력을 분석하고 미래기술전략을 도출하기 위해 논문·특허정보를 기반한 정량평가(활동력, 기술력, 포트폴리오)와 미래기술 예측을 수행하였다. 수자원 분야 기술은 2017년 과학기술정보통신부가 승인한 45대 기후기술 분류체계를 기본으로 하며, 적응 부문에서 '물관리 기술'과 '기후변화 예측 및 모니터링 기술'을 대상으로 하였다. 분석을 위해 수자원 분야 기술을 주요 5개국(한국, 중국, 일본, 미국, EU) 대상으로 수행하였으며, 데이터 기간은 2009년부터 2020년까지 총 12년간이다. 기술의 미래예측하기 위해 Bass 모형, Logistic 모형, Gompertz 모형 등을 활용하였으며, 향후 기술을 전망하고자 한다. 본 분석에서 수행하는 수자원 분야 기술예측은 탄소중립 실현을 위한 미래사회에 대비하고, 기술개발에 대한 불확실성을 감소시킬 수 있을 것으로 기대된다.

• IE interfaces
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• v.14 no.2
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• pp.190-197
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• 2001

Growth curves including Logistic and Gompertz functions are widely used in forecasting the market demand. To estimated the parameters of those functions, we use the non-linear least square method. However, it is difficult to set up the starting points for each parameter. If a wrong starting point is selected, the result reveals the local optimum or does not converge to a certain value. The purpose of this paper is to resolve the problem of selecting a starting point. Especially, rescaling the market data using the national economic index make it possible to figure out the range of parameters and to utilize the grid search method. Applications to some real data are also included.

• Journal of Wetlands Research
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• v.17 no.4
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• pp.436-446
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• 2015

It is suggested investigating method about the existing state of demand in this study. The total demand of 357 water amenity zones in 2014 is estimated based on the growth curve models. The effects of population density and distances between water amenity zones and metropolises populated over 1 million are investigated on each river system. The suitability like RMSE and MAPE of logistic and gompertz models are considered to select more suitable model for each water amenity zone. Demand for water amenity zones in 2014 is seemed to be rather high at Han Gang river system and Chungcheongbukdo after analyzing. The influence of population density is rarely effective except Geum Gang river system. The influence of metropolis on the demand for water amenity zones is higher at Geum Gang river system than others.

• International Area Studies Review
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• v.13 no.3
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• pp.331-359
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• 2009

We forecast the performance of the Korean biotechnology industry by adopting similar development paths taken by the U.S. biotechnology and Korean ICT industries. Our long-term forecasting techniques predict that Korean BT market size will increase from 3.7 billion to 10.8 billion U.S. dollars by year 2030. The pharmaceutical industry, one of major bio-subindustries, is expected to dominate Korean BT market in the long-run. Also, the relative portion of the exports in the Korean BT industry will be larger and thus the export-oriented government policy is required for the long-run growth of the Korean BT industry. Since the Korean ICT industry has already slowed down in the development, Korean BT industry is likely to catch up with ICT industry in the near future.

• 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.