• Journal of Korea Port Economic Association
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• v.24 no.4
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• pp.313-327
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• 2008

The purpose of this paper is to show the empirical measurement way for predicting the seaport efficiency by using SBM with Wilcoxson signed-rank test under CRS(constant returns to scale) condition for 20 Korean ports during 1994-2003 for 2 inputs(birthing capacity, cargo handling capacity) and 3 outputs(Export and Import Quantity, Number of Ship Calls, Port Revenue). The main empirical results of this paper are as follows. First, forecasting data have well reflected the real data according to the Wilcoxon signed rank test, because p values have exceeded the 0.05 significance level. Second, SBM has shown the effectiveness for predicting the ports efficiency even though the predicting powers are different according to the levels of p values. The policy implication to the Korean seaports and planner is that Korean seaports should introduce the new methods like SBM method with Wilcoxon signed rank test for predicting the port performance and enhancing the efficiency.

• Journal of Korean Society for Atmospheric Environment
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• v.18 no.4
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• pp.327-334
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• 2002

The work presents sensitivity and uncertainty analysis of 2-compartment model for the evaluation of indoor radon pollution in a house. Effort on the development of such model is directed towards the prediction of the generation and transfer of radon in indoor air released from groundwater. The model is used to estimate a quantitative daily human exposure through inhalation of such radon based on exposure scenarios. However, prediction from the model has uncertainty propagated from uncertainties in model parameters. In order to assess how model predictions are affected by the uncertainties of model inputs, the study performs a quantitative uncertainty analysis in conjunction with the developed model. An importance analysis is performed to rank input parameters with respect to their contribution to model prediction based on the uncertainty analysis. The results obtained from this study would be used to the evaluation of human risk by inhalation associated with the indoor pollution by radon released from groundwater.

• Geomechanics and Engineering
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• v.31 no.2
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• pp.129-147
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• 2022

The properties of soil are naturally highly variable and thus, to ensure proper safety and reliability, we need to test a large number of samples across the length and depth. In pile foundations, conducting field tests are highly expensive and the traditional empirical relations too have been proven to be poor in performance. The study proposes a state-of-art Particle Swarm Optimization (PSO) hybridized Artificial Neural Network (ANN), Extreme Learning Machine (ELM) and Adaptive Neuro Fuzzy Inference System (ANFIS); and comparative analysis of metaheuristic models (ANN-PSO, ELM-PSO, ANFIS-PSO) for prediction of bearing capacity of pile foundation trained and tested on dataset of nearly 300 dynamic pile tests from the literature. A novel ensemble model of three hybrid models is constructed to combine and enhance the predictions of the individual models effectively. The authenticity of the dataset is confirmed using descriptive statistics, correlation matrix and sensitivity analysis. Ram weight and diameter of pile are found to be most influential input parameter. The comparative analysis reveals that ANFIS-PSO is the best performing model in testing phase (R² = 0.85, RMSE = 0.01) while ELM-PSO performs best in training phase (R² = 0.88, RMSE = 0.08); while the ensemble provided overall best performance based on the rank score. The performance of ANN-PSO is least satisfactory compared to the other two models. The findings were confirmed using Taylor diagram, error matrix and uncertainty analysis. Based on the results ELM-PSO and ANFIS-PSO is proposed to be used for the prediction of bearing capacity of piles and ensemble learning method of joining the outputs of individual models should be encouraged. The study possesses the potential to assist geotechnical engineers in the design phase of civil engineering projects.

• Journal of Biosystems Engineering
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• v.21 no.2
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• pp.198-207
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• 1996

To measure the moisture content, protein and viscosity of brown and milled rice with Near Infrared Reflectance(NIR) analyzer, the comparison and analysis of the data from the chemical analysis and NIR analyzer were conducted. The purpose of this study is to find out the fundamental data required for the prediction of rice qualify and taste rank, and to develop a measuring method of constituents and physical characteristics of domestic rice with NIR analyzer. The important results can be summarized as follows. 1. The $r^2$ and SEC of moisture calibration from brown rice powder were 0.87 and 0.09 respectively, those of milled rice powder were 0.95 and 0.08 respectively. 2. The $r^2$ and SEC of protein calibration from brown rice powder were 0.83 and 0.20 respectively, those of milled rice powder were 0.86 and 0.20 respectively. 3. The $r^2$ and SEC of viscosity calibration from brown rice powder were 0.36 and 15.50 respectively, those of milled rice powder were 0.55 and 12.98 respectively. Further study is required to develop better prediction model for viscosity. It is necessary the continuous study including wavelength selection, because $r^2$ is small for practical use. 4. The regression equation for one rice variety was nearly coincident with other. Therefore, it is required that the prediction model should be developed for the all rice samples.

• The Korean Journal of Ecology
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• v.28 no.5
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• pp.255-260
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• 2005

We investigated interventions by mother Jeju ponies on Jeju Island, Korea, to determine whether mothers assisted their offspring to attain higher status within the dominance hierarchy. Because dominance rank is important within each gender, we predicted that mothers would be more likely to intervene when their foals were play-fighting with foals of the same gender. A total of 173 play-fighting events were recorded from March to October 1998 and from April to October 1999. Of these, foals were more likely to play-fight with a foal of the same gender as with a foal of the opposite gender (120 versus 53 occurrences, respectively). A mother of one of the foals that were play-fighting intervened in 17 of these interactions. Contrary to the prediction, a mare was more likely to intervene when opposite genders interacted than when the same gender interacted. Analyzing interactions between the opposite genders further, mothers were equally likely to intervene when a daughter was play-fighting with a male foal as when a son was play-fighting with a female foal. Hence, mothers were not more protective of daughters than sons. Mothers that were in the younger age class ($2\sim11$ years old) were as likely to intervene as those in the elder age class ($17\sim25$ years old). However, all foals that were harassed were offspring of mothers in the younger, more subordinate age class. intervention directly maintains the dominance rank of the intervening mother, and may indirectly assist the intervening mother's foal to achieve a higher dominance rank. By discouraging their foals from play-fighting with the opposite genders, dominant mothers may be encouraging their foals to play-fight with the same gender and participate in establishing its own dominance rank.

• Journal of KIISE
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• v.45 no.1
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• pp.15-21
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• 2018

Low-Rank Representation (LRR) based methods are widely used in many practical applications, such as face clustering and object detection, because they can guarantee high prediction accuracy when used to constructing graphs in graph - based semi-supervised learning. However, in order to solve the LRR problem, it is necessary to perform singular value decomposition on the square matrix of the number of data points for each iteration of the algorithm; hence the calculation is inefficient. To solve this problem, we propose an improved and faster LRR method based on the recently published Fast LRR (FaLRR) and suggests ways to introduce and optimize additional constraints on the underlying optimization goals in order to address the fact that the FaLRR is fast but actually poor in classification problems. Our experiments confirm that the proposed method finds a better solution than LRR does. We also propose Fast MLRR (FaMLRR), which shows better results when the goal of minimizing is added.

• Journal of Korea Game Society
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• v.21 no.4
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• pp.3-12
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• 2021

In this study, models for predicting the final result of League of Legends game were constructed for each rank using data from the first 10 minutes of the game. Variable importance was extracted from the prediction models to derive strategic direction in early phase of the game. As a result, it was possible to predict final results with over 70% accuracy in all ranks. It was found that early game advantage tends to lead to the final win and this tendency appeared stronger as it goes to challenger ranks. Kill(death) was found to be the most influential factor for win, however, there were also variables whose importance rank changed according to rank. This indicates there is a difference in the strategic direction in the early stage of the game depending on the rank.

• Journal of Industrial Technology
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• v.18
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• pp.187-193
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• 1998

In this study, about the fatigue life of welded structure material under fluctuation loading, the prediction life which is produced by using the Histogram Recorder System was compared with the experimental life which is produced by the RMC model which is imported by conception of equivalent stress. In this result, this is represented few difference by comparing prediction life which is produced by damage analysis depended on Miner's rule, by using the Histogram Recorder System, with experimental life which is produced by the RMC load model which is imported by conception of equivalent of stress, therefore fatigue life is easily predicted by using Histogram Recorder System, and result of prediction has equivalent accuracy with other method which is more complex than the Histogram Recorder System. Besides the damage which is produced by stress which is high thirty percentage rank in the stress range of damage inducing, is nearly equal to the damage which is induced the rest of seventy percentage, there fore we can see that damage accumulation which is induced few time overload which is effected welded structure material is great.

• 한국연소학회:학술대회논문집
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• 2013.06a
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• pp.87-90
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• 2013

In pulverized coal fired boilers, slagging and fouling may cause significant effect on the operational life of boiler. As increasing a consumption of low rank coal, slagging and fouling are main issues in pulverized coal combustion. This study predicts ash deposition propensity in a 0.7 MW pilot-scale furnace. Slagging model is employed as a User-Defined Function (UDF) of FLUENT and validated against measurement and prediction. The results show good agreement compared with experiment. There is need to development of a pulverized coal combustion and slagging analysis at low coal.

• Communications for Statistical Applications and Methods
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• v.19 no.3
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• pp.367-379
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• 2012

In baseball rankings, prediction has been a subject of interest for baseball fans. To predict these rankings, (based on 2011 data from Korea Professional Baseball records) the arithmetic mean method, the weighted average method, principal component analysis, and principal component regression analysis is presented. By standardizing the arithmetic average, the correlation coefficient using the weighted average method, using principal components analysis to predict rankings, the final model was selected as a principal component regression model. By practicing regression analysis with a reduced variable by principal component analysis, we propose a rank predictability model of a pitcher part, a batter part and a pitcher batter part. We can estimate a 2011 rank of pro-baseball by a predicted regression model. By principal component regression analysis, the pitcher part, the other part, the pitcher and the batter part of the ranking prediction model is proposed. The regression model predicts the rankings for 2012.