• Journal of Korean Society of Forest Science
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• v.100 no.1
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• pp.62-69
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• 2011

Six commonly used non-linear growth functions were fitted to individual tree height-dbh data of eight major tree species measured by the $5^{th}$ National Forest Inventory in Chungcheong province. A total of 2,681 trees were collected from permanent sample plots across Chungcheong province. The available data for each species were randomly splitted into two sets: the majority (90%) was used to estimate model parameters and the remaining data (10%) were reserved to validate the models. The performance of the models was compared and evaluated by $R^2$, RMSE, mean difference (MD), absolute mean difference (AMD) and mean difference(MD) for diameter classes. The combined data (100%) were used for final model fitting. The results showed that these six sigmoidal models were able to capture the height-diameter relationships and fit the data equally well, but produced different asymptote estimates. Sigmoidal growth models such as Chapman-Richards, Weibull functions provided the most satisfactory height predictions. The effect of model performance on stem volume estimation was also investigated. Tree volumes of different species were computed by the Forest Resources Evaluation and Prediction Program using observed range of diameter and the predicted tree total height from the six models. For trees with diameter less than 30 cm, the six height-dbh models produced very similar results for all species, while more differentiation among the models was observed for large-sized trees.

• Journal of Digital Convergence
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• v.19 no.11
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• pp.445-456
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• 2021

The purpose of this study is to identify the importance of variables affecting women's golf wear sales with macroeconomic variables and consumer selling prices that affect consumers' purchasing behavior, and to propose a price strategy to increase sales of golf wear. Data of domestic women's golf wear brands were analyzed using decision tree algorithms and ensemble. Consumer selling price is the most significant factors in terms of sales volume for T-shirt, pants and knit, while categories were found to be the most important factors in addition to consumer sales prices for skirt and one piece dress. These findings suggest that items have different economic variables that affect consumers' purchasing behavior, suggesting that sales and profits can be maximized through appropriate price strategies.

• Journal of Korean Society of Forest Science
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• v.112 no.1
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• pp.83-92
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• 2023

This study was established to investigate the site environment of mixed forests in Korea and to estimate the growth and yield of stands using national forest resources inventory data. The growth of mixed forests was derived by applying the Chapman-Richards model with diameter at breast height (DBH), height, and cross-sectional area at breast height (BA), and the yield of mixed forests was derived by applying stepwise regression analysis with factors such as cross-sectional area at breast height, site index (SI), age, and standing tree density per ha. Mixed forests were found to be growing in various locations. By climate zone, more than half of them were distributed in the temperate central region. By altitude, about 62% were distributed at 101-400 m. The fitness indexes (FI) for the growth model of mixed forests, which is the independent variable of stand age, were 0.32 for the DBH estimation, 0.22 for the height estimation, and 0.18 for the basal area at breast height estimation, which were somewhat low. However, considering the graph and residual between the estimated and measured values of the estimation equation, the use of this estimation model is not expected to cause any particular problems. The yield prediction model of mixed forests was derived as follows: Stand volume =-162.6859+6.3434 ∙ BA+9.9214 ∙ SI+0.7271 ∙ Age, which is a step- by-step input of basal area at breast height (BA), site index (SI), and age among several growth factors, and the determination coefficient (R²) of the equation was about 96%. Using our optimal growth and yield prediction model, a makeshift stand yield table was created. This table of mixed forests was also used to derive the rotation of the highest production in volume.

• Journal of Korean Society of Forest Science
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• v.106 no.2
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• pp.267-273
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• 2017

This study was conducted to construct a empirical yield table for Pinus densiflora in real forest. Since existing normal yield tables have been derived by studying and analyzing communities in ideal environment for tree growth, those tables provide more over-estimated values than ones from real forest. Because of this, there are some difficulties to apply the tables to empirical forest except for normal forest. In this study, therefore, we estimated stand growth for real forest on P. densiflora as the representative species of conifers. We used 1,957 sample plot data of P. densiflora in central Korea from National Forest Inventory (NFI) system, and analyzed through estimation, recovery and prediction in order by using Weibull function as a diameter distribution model. Weilbull and Schumacher models were applied for estimating mean DBH and mean basel area and it was found that the site index for P. densiflora in central Korea ranges from 8 to 14 at reference age 30. According to site 12 in the stand yield table, the Mean Annual Increment (MAI) of P. densiflora was $4.42m^3/ha$ at 30 years of age. Compared to existing volume table constructed before, it is showed that MAI of this study were lower. According to the paired t-test that is conducted with the gap of volume values between normal forest and real forest by site index and age, the P-value was less than 0.001 which is recognized to have a statistically significant difference. Based on the results in this study, it is considered to be helpful for practical management and management policy on P. densiflora in central Korea.

• Journal of Korean Society of Forest Science
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• v.90 no.6
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• pp.725-733
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• 2001

In this study, the relationship between growth factors for Pinus densiflora stands in Anmyun-Island was analyzed and dynamic growth model was prepared. A total of 96 sample plots was investigated in which dbh and height of individual trees were measured. From these plot data, quadratic mean dbh, mean height, dominant tree height, stem number per ha, basal area per ha and volume per ha were estimated. Several regression equations between growth factors were derived using NLIN and REG procedure of SAS. And dynamic growth model, in which the equations were interactively linked, was prepared for the prediction of stand growth and yield under different management regime. The predictions of dynamic growth model were found to be coincided with general growth principles. The dynamic growth model was considered as adequate for predicting growth and yield of Pinus densiflora stand in Anmyun-Island. In practice, the dynamic growth model can be applied for predicting the growth and development of stand for various forest treatments and for decision-making in forest management.

• Journal of Korean Society of Forest Science
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• v.108 no.4
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• pp.574-581
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• 2019

The present study analyzed the productivity and cost of winching operations for evaluating the efficiency of a tractor-attached winch in a Pinus densiflora thinning site located in the Yangyang County of Gangwon-do. The mean yarding distance and mean timber volume were 29 m and 0.15 ㎥, respectively. In the 95 cycles of yarding operations, the uphill and downhill yarding operations constituted 51% and 49%, respectively, of the total yarding operations. The productivity of the uphill yarding operation was 2.28 ㎥/h, and the productivity of the downhill yarding operation was 1.89 ㎥/h. The findings of this study revealedthat productivity would increase by 0.5 ㎥/h when the rate of utilization of the machine is increased to 80% by reducing the operational delay time. The cost of the downhill yarding operation was 44,116 KRW/㎥, whereas that of the uphill yarding operation was 53,369 KRW/㎥. The difference in cost resulted from the difference in the number of yarding stems (stems/cycle). Furthermore, the results of the multiple linear regression equation developed for predicting the yarding operation times showed that productivity was significantly affected by working conditions such as yarding distance (m), the number of stems per cycle (stems/cycle), and the terrain slope (%) in the uphill and downhill yarding operations. Further research is required for developing an accurate prediction model equation according to a yarding direction.