• 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 Electrical Engineering and Technology
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• v.12 no.2
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• pp.969-980
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• 2017

Galloping is one of the most serious vibration problems in transmission lines. Power lines can be extensively damaged owing to aerodynamic instabilities caused by ice accretion. In this study, the accident probability induced by galloping phenomenon was analyzed using logistic regression analysis. As former studies have generally concluded, main factors considered were local weather factors and physical factors of power delivery systems. Since the number of transmission towers outnumbers the number of weather observatories, interpolation of weather factors, Kriging to be more specific, has been conducted in prior to forming galloping accident estimation model. Physical factors have been provided by Korea Electric Power Corporation, however because of the large number of explanatory variables, variable selection has been conducted, leaving total 11 variables. Before forming estimation model, with 84 provided galloping cases, 840 non-galloped cases were chosen out of 13 billion cases. Prediction model for accidents by galloping has been formed with logistic regression model and validated with 4-fold validation method, corresponding AUC value of ROC curve has been used to assess the discrimination level of estimation models. As the result, logistic regression analysis effectively discriminated the power lines that experienced galloping accidents from those that did not.

• Journal of The Geomorphological Association of Korea
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• v.23 no.2
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• pp.109-125
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• 2016

This study aims to identify the landslide susceptible zones of Boeun area and provide reliable landslide susceptibility maps by applying different modeling methods. Aerial photographs and field survey on the Boeun area identified landslide inventory map that consists of 388 landslide locations. A total ofseven landslide causative factors (elevation, slope angle, slope aspect, geology, soil, forest and land-use) were extracted from the database and then converted into raster. Landslide causative factors were provided to investigate about the spatial relationship between each factor and landslide occurrence by using fuzzy set and logistic regression model. Fuzzy membership value and logistic regression coefficient were employed to determine each factor's rating for landslide susceptibility mapping. Then, the landslide susceptibility maps were compared and validated by cross validation technique. In the cross validation process, 50% of observed landslides were selected randomly by Excel and two success rate curves (SRC) were generated for each landslide susceptibility map. The result demonstrates the 84.34% and 83.29% accuracy ratio for logistic regression model and fuzzy set model respectively. It means that both models were very reliable and reasonable methods for landslide susceptibility analysis.

• Journal of Animal Science and Technology
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• v.45 no.4
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• pp.509-516
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• 2003

Growth curves were estimated for 1083 female Korean cattle raised in Daekwanryeong branch, National Livestock Research Institute (NLRI). Comparisons were made among various growth curve models for goodness of fit for the growth of the cows. Estimated growth curve functions were $W_t=370.2e^{-2.208e^{-0.00327t}$ for Gompertz model, for von Bertalanffy model, and $W_t=341.2(1+5.652e^{-0.00524t})^{-1}$ for Logistic model. Ages at inflection estimated from Gompertz model, von Bertalanffy model and Logistic model were 242.2 days, 191.5 days, and 330.5 days respectively, body weight at inflection were 136kg, 115kg, and 170kg, and daily gain at inflection were 0.445kg, 0.451kg, and 0.446kg. The predicted weights by ages from Gompertz model, von Bertalanffy model, and Logistic model were onsistently overestimated at birth weight and underestimated at 36 month weight. The von Bertalanffy model which had a variable point of inflection fit the data best.

• Journal of Animal Science and Technology
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• v.50 no.5
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• pp.601-612
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• 2008

This study was conducted to figure out how the shape of Hanwoo changes over time, examine the rank correlations between the carcass traits which are the selection traits and parameters of growth curve, and determine the correlation between body shape and carcass. Body weight, body measurements and carcass traits were measured from 161 castrated Hanwoo, and 12 growth traits and 5 carcass traits were investigated in total. The logistic model(Nelder, 1961) used for the estimation of growth curve parameters and growth characteristics at inflection point were calculated by these growth curve parameters. The value of this parameter was greatest for pinbone width, which suggests that it is an early ripening trait, while it was lowest for chest girth, suggesting it to be a late ripening trait. The rank correlations of chest depth, chest width, and hip width with backfat thickness steadily increased from 6 to 24 months, while the rank correlations of other traits decreased after 18 months until 24 months of age. Only phenotypic records were analyzed in this study, but for examine the genetic changes over growth phase in Hanwoo, if another additional genetic analysis like as estimation of genetic parameters should achieve, body measurements may be useful traits in proven bull selection.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2008.11a
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• pp.93-96
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• 2008

This research performed strength improvement analysis after evaluating strength characteristics by estimated temperatures to evaluate the real time strength performance of 50 to 80 MPa high performance concrete equipped with heat resistance, and the results are as follows. The lesser W/B and the lesser target slump flow value difference, compression strength was shown to increase, and the more curing temperature becomes, the strength increased accordingly. According to the correlation review result of strength improvement analysis by estimated temperature change performed using logistic analysis model, the compression strength value predicted with logistic curve expression and the compression strength value measured in experiment were shown to have similar correlation, and the strength improvement analysis value by logistic model was shown to be estimated good when W/B is high.

• Journal of the Korea Institute of Building Construction
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• v.6 no.3 s.21
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• pp.99-105
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• 2006

In this paper, the estimation of compressive strength of concrete incorporating fly ash subjected to high temperature is discussed. Ordinary Portland cement and fly ash cement(30% of fly ash) were used, respectively. Water to binder ration ranging from 30% to 60% and curing temperature ranging from $20^{\circ}C{\sim}65^{\circ}C$ were also adopted for the experimental parameters. According to results, at the high temperature, FAC had higher strength development at early age than OPC concrete and it kept its high strength development at later age due to accelerated pozzolanic reaction subjected to high temperature. For strength estimation, Logistic model based on maturity equation and Carino model based on equivalent age were applied to verify the availability of estimation model. It shows that fair agreements between calculated values and measured values were obtained evaluating compressive strength with logistic curve. The application of logistic model at high temperature had remarkable deviations in the same maturity. Whereas, the application of Carino model showed good agreements between calculated values and measured ones regardless of type of cement and W/B. However, some correction factors should be considered to enhance the accuracy of strength estimation of concrete.

• Journal of Environmental Science International
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• v.16 no.3
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• pp.347-355
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• 2007

In this paper, estimation of the compressive strength of the concrete incorporating blast furnace slag subjected to high temperature was discussed. Ordinary Portland cement and blast furnace slag cement (BSC;30% of blast furnace slag) were used, respectively. Water to binder ratio ranging from 30% to 60% and curing temperature ranging from $20^{\circ}C{\sim}65^{\circ}C$ were also chosen for the experimental parameters, respectively. At the high temperature, BSC had higher strength development at early age than OPC concrete and it kept its high strength development at later age due to accelerated latent hydration reaction subjected to high temperature. For the strength estimation, the Logistic model based on maturity equation and the Carino model based on equivalent age were applied to verify the availability of estimation model. It was found that fair agreements between calculated values and measured values were obtained evaluating compressive strength with logistic curve. The application of logistic model at high temperature had remarkable deviations in the same maturity. Whereas, the application of Carino model showed good agreements between calculated values and measured ones regardless of type of cement and W/B. However, some correction factors should be considered to enhance the accuracy of strength estimation of concrete.

• Journal of The Geomorphological Association of Korea
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• v.26 no.2
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• pp.1-14
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• 2019

This study analyzed the relativity between block stream and talus distributions by employing a likelihood ratio approach. Possible distribution sites for each debris slope landform were extracted by applying a spatial integration model, in which we combined fuzzy set model, Bayesian predictive model, and logistic regression model. Moreover, to verify model performance, a success rate curve was prepared by cross-validation. The results showed that elevation, slope, curvature, topographic wetness index, geology, soil drainage, and soil depth were closely related to the debris slope landform sites. In addition, all spatial integration models displayed an accuracy of over 90%. The accuracy of the distribution potential area map of the block stream was highest in the logistic regression model (93.79%). Eventually, the accuracy of the distribution potential area map of the talus was also highest in the logistic regression model (97.02%). We expect that the present results will provide essential data and propose methodologies to improve the performance of efficient and systematic micro-landform studies. Moreover, our research will potentially help to enhance field research and topographic resource management.

• Proceedings of the Korea Concrete Institute Conference
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• 2000.04a
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• pp.163-168
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• 2000

In this paper, removal times of from from concrete using OPC( Ordinary Portland Cement) and BSC(Blast-furnace Slag cement) are suggested by appling logistic curve, which evaluates the strength development of concrete with maturity. W/B, kinds of cement and curing temperatures are selected as test parameters. According to the results, the estimation of strength development by logistic curve has a good agreement between calculated values. As for the removal time of from suggested in this paper, as W/B increase, curing temperature decrease and BSC in used, removal they times of from are shown to be kept longer. Removal times of from from concrete using OPC suggested in this paper are shorter by about 2~3day than those of standard specifications provided in KCI in the rang of over $20^{\circ}C$, while they takes 4~5 day shorter compared with those of standard specifications Provided in KCI in the range of 10~$20^{\circ}C$. Removal times of from for concrete using OPC are longer than those using BSC by about 1 day.