• 수도
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• s.25
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• pp.28-39
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• 1981

• Water for future
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• v.36 no.1
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• pp.124-128
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• 2003

• Journal of Korean Society of Forest Science
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• v.112 no.2
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• pp.209-216
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• 2023

This study aimed to use national forest inventory data to develop a forest productivity index and yield prediction model of a Tilia amurensis stand. The site index displaying the forest productivity of the Tilia amurensis stand was developed as a Schumacher model, and the site index classification curve was generated from the model results; its distribution growth in Korea ranged from 8-16. The growth model using age as an independent variable for breast height and height diameter estimation was derived from the Chapman-Richards and Weibull model. The Fitness Indices of the estimation models were 0.32 and 0.11, respectively, which were generally low values, but the estimation-equation residuals were evenly distributed around 0, so we judged that there would be no issue in applying the equation. The stand basal area and site index of the Tilia amurensis stand had the greatest effect on the stand-volume change. These two factors were used to derive the Tilia amurensis stand yield model, and the model's determination coefficient was approximately 94%. After verifying the residual normality of the equation and autocorrelation of the growth factors in the yield model, no particular problems were observed. Finally, the growth and yield models of the Tilia amurensis stand were used to produce the makeshift stand yield table. According to this table, when the Tilia amurensis stand is 70 years old, the estimated stand-volume per hectare would be approximately 208 m³ . It is expected that these study results will be helpful for decision-making of Tilia amurensis stands management, which have high value as a forest resource for honey and timber.

• The KIPS Transactions:PartB
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• v.15B no.4
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• pp.323-330
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• 2008

Since complex diseases are caused by interactions of multiple genes, traditional statistical methods are limited in its power to predict the onset of a complex disease. Recently new approaches using machine learning techniques are introduced. Neural nets are a suitable model to find patterns in complex data. When large amount of data are fed into a neural net, however, it takes a long time for learning and finding patterns. In this study we suggest a new model that combines the set association, which is a statistical technique to find important SNPs associated with complex diseases, and neural network. We experiment with SNP data related to asthma to test the effectiveness of our model. Our model shows higher prediction accuracy and shorter execution time than neural net only. We expect our model can be used effectively to predict the onset of other complex diseases.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.4
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• pp.83-92
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• 2022

Due to the uncertainty in the order of the integrated model, the SARIMA-LSTM model, SARIMA-SVR model, LSTM-SARIMA model, and SVR-SARIMA model are constructed respectively to determine the best-combined model for forecasting the China-Russia trade turnover. Meanwhile, the effect of the order of the combined models on the prediction results is analyzed. Using indicators such as MAPE and RMSE, we compare and evaluate the predictive effects of different models. The results show that the SARIMA-LSTM model combines the SARIMA model's short-term forecasting advantage with the LSTM model's long-term forecasting advantage, which has the highest forecast accuracy of all models and can accurately predict the trend of China-Russia trade turnover in the post-epidemic period. Furthermore, the SARIMA - LSTM model has a higher forecast accuracy than the LSTM-ARIMA model. Nevertheless, the SARIMA-SVR model's forecast accuracy is lower than the SVR-SARIMA model's. As a result, the combined models' order has no bearing on the predicting outcomes for the China-Russia trade turnover time series.

• Journal of Korea Water Resources Association
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• v.42 no.12
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• pp.1053-1067
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• 2009

The objective of this study is to develop an efficient and accurate quadratic finite element model based on Streamline Upwind/Petrov Galerkin (SU/PG) scheme for analyzing and predicting two dimensional flow features in complex natural rivers. For a development of model, quadratic tin, quadrilateral and mixed elements as well as linear tin, quadrilateral and mixed elements were used in the model. Also, this model was developed through reinforcement of Gauss Quadrature which was necessary to integral of governing equation. Several tests for bottom-rising channel and U-type channel were performed for the purpose of validation and verification of the developed model. Such results showed that solutions of second order elements are better accurate and improved than those of linear elements. Results obtained by the developed model and RMA-2 model are compared, and the results for the developed model were better accurate than those of RMA-2 model. In the future if the developed model is applied in natural rivers, it can provide better accurate results than those of existing model.

• Journal of the Korean Association of Oral and Maxillofacial Surgeons
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• v.34 no.5
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• pp.555-561
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• 2008

Purpose: The goal of this study was to develop a technique for creating a computerized composite maxillofacial-dental model, based on point-based surface best fit algorithm and to test its accuracy. The computerized composite maxillofacial-dental model was made by the three dimensional combination of a 3-dimensional (3D) computed tomography (CT) bone model with digital dental model. Materials and Methods: This integration procedure mainly consists of following steps : 1) a reconstruction of a virtual skull and digital dental model from CT and laser scanned dental model ; 2) an incorporation of dental model into virtual maxillofacial-dental model by point-based surface best fit algorithm; 3) an assessment of the accuracy of incorporation. To test this system, CTs and dental models from 3 volunteers with cranio-maxillofacial deformities were obtained. And the registration accuracy was determined by the root mean squared distance between the corresponding reference points in a set of 2 images. Results and Conclusions: Fusion error for the maxillofacial 3D CT model with the digital dental model ranged between 0.1 and 0.3 mm with mean of 0.2 mm. The range of errors were similar to those reported elsewhere with the fiducial markers. So this study confirmed the feasibility and accuracy of combining digital dental model and 3D CT maxillofacial model. And this technique seemed to be easier for us that its clinical applicability can good in the field of digital cranio-maxillofacial surgery.

• The Journal of the Korean dental association
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• v.44 no.2 s.441
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• pp.115-122
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• 2006

Objective : The purpose of this study was to evaluate the dimensional errors between real tooth, 3D CT image and CARP model. Materials and Methods : Two maxilla and two mandible block bones with intact teeth were taken from two cadavers. Computed tomography was taken either in dry state and in wet state. After then, all teeth were extracted and the dimensions of the real teeth were measured using a digital caliper at mesio-distal and bucco-lingual width both in crown and cervical portion. 3D CT image was generated using the V-works $4.0^{TM}$ (Cybemed Inc., Seoul, Korea) software. Twelve teeth were randomly selected for CARP model fabrication. All the measurements of 3D Ct images and CARP models were made in the same manner of the real tooth group. Dimensional errors between real tooth, 3D CT image model and CARP model was calculated. Results : 1) Average of absolute error was 0.199 mm between real teeth and 3D CT image model, 0.169 mm between 3D CT image model and CARP model and 0.291 mm between real teeth and CARP model, respectively. 2) Average size of 3D CT image was smaller than real teeth by 0.149 mm and that of CARP model was smalier than 3D CT image model by 0.067mm. Conclusion : Within the scope of this study, CARP model with the 0.291 mm average of absolute eror can aid to enhance the success rate cf autogenous tooth transplantation due to the increased accuracy of recipient bone and donor tooth.

• Journal of Korea Water Resources Association
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• v.49 no.2
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• pp.165-175
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• 2016

In order to examine the applicability, the evaporation estimation approaches based on solar radiation are classified into 3 different model groups (Model groups A, B, and C) in this study. Each group is tested in the 6 study stations (Seoul, Daejeon, Jeonju, Busan, Mokpo, and Jeju). The model parameters of each model group are estimated and verified with measured pan evaporation data. The applicability of verified model groups are compared with results of Penman (1948) combination approach. Nash-Sutcliffe (N-S) efficiency coefficients greater than 0.663 in all study stations indicate satisfactory estimates of evaporation. On the other hand, in the model verification process, N-S efficiency coefficients greater than 0.526 in all study stations indicate also satisfactory estimates of evaporation. However, N-S efficiency coefficients in all study cases except Model groups B and C in Busan are less than those of Penman (1948) combination approach. Therefore, it is concluded in this study that the evaporation estimation approaches based on solar radiation have capability to replace Penman (1948) combination approach for the estimation of evaporation in case that some meteorological data (wind speed, relative humidity) are missing or not measured.

• Korean Journal of Hydrosciences
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• v.4
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• pp.33-49
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• 1993

The Purpose of this study is to classify existing hysteresis models and to discuss a possibility of a new type of the hysteresis model. The existing hysteresis models are classified into three types: the interpolation model, the scaling model and the domain model, of which only domain model is to simulate hysteresis curves based on the theoretical approach, It is useful to develop a hysteresis model that requires only one branch of hysteresis curves for the model calibration because obtaining hysteresis curves by experiments is expensive and time-concept by many investigators, however their models are not successful to accurately simulate real data of Rubicon Sandy Loam and Dune Sand. There is a possibility that a new model is based on the dependent domain concept considering the weighting factor, $P_a$($\theta$), which accounts for the pore blockage effect against air entry. Conclusively, a new model where the weighting factor $P_a$($\theta$) in Model III-1 (Mualem, 1984) reduces to a known variable through an appropriate method is an alternative model which required only one branch of main curves for the model calibration.