• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.53 no.4
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• pp.471-475
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• 2017

This study aims to suggest the methodology to improve to estimate back-calculated fish growth parameters using weighted average. It is to contribute to correct errors in the calculation of back-calculated growth equation with unequal numbers of sample by age. If the numbers of sample were evenly collected by age, each back-calculated length at age was equal between arithmetic and weighted averages. However, most samples cannot be evenly collected by age in reality because of different catchability by fishing gear and limitation of environment condition. Therefore, the estimation of back-calculated length by weighted average method is essential to calculate growth parameters. There were some published growth equations from back-calculated length using a simple arithmetic average with different numbers of samples by age when searching for back-calculated growth equations from 91 relevant papers. In this study, the process of deriving growth equation was investigated and two different average calculations were applied to a fish growth equation, for example of Acheilognathus signifer. Growth parameters, such as $L_{\infty}$, k and $t_0$, were estimated from two different back-calculated averages and the growth equations were compared with growth performance index. Based on the correction of back-calculated length using weighted average by age, the changes by female and male were -14.19% and -5.23% for $L_{\infty}$, and 59.28% and 18.91% for k, respectively. The corrected growth performance index by weighted average improved at 7.05% and 2.46% by female and male, respectively, compared to the arithmetic averages.

• Structural Engineering and Mechanics
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• v.54 no.3
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• pp.561-577
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• 2015

The main objective of this paper is to study the dynamic load allowance (DLA) calculation methods for bridges according to the dynamic response curve. A simply-supported concrete bridge with a smooth road surface was taken as an example. A half-vehicle model was employed to calculate the dynamic response of deflection and bending moment in the mid-span section under different vehicle speeds using the vehicle-bridge coupling method. Firstly, DLAs from the conventional methods and code provisions were analyzed and critically evaluated. Then, two improved computing approaches for DLA were proposed. In the first approach, the maximum dynamic response and its corresponding static response or its corresponding minimum response were selected to calculate DLA. The second approach utilized weighted average method to take account of multi-local DLAs. Finally, the DLAs from two approaches were compared with those from other methods. The results show that DLAs obtained from the proposed approaches are greater than those from the conventional methods, which indicate that the current conventional methods underestimate the dynamic response of the structure. The authors recommend that the weighted average method based on experiments be used to compute DLAs because it can reflect the vehicle's whole impact on the bridge.

• Phonetics and Speech Sciences
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• v.2 no.4
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• pp.145-151
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• 2010

In this paper, a robust feature compensation method is proposed for improving the performance of speech recognition. The proposed method is incorporated into the auto-regressive moving average (ARMA) based feature compensation. We employ variable weights for the ARMA filter according to the degree of speech activity, and pass the normalized cepstral sequence through the weighted ARMA filter. Additionally when normalizing the cepstral sequences in training, the cepstral means and variances are estimated from total training utterances. Experimental results show the proposed method significantly improves the speech recognition performance in the noisy and reverberant environments.

• Geomechanics and Engineering
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• v.36 no.1
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• pp.83-97
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• 2024

It is important to make reasonable prediction about the long-term deformation of high rockfill geostructures. However, the deformation is usually underestimated using the rockfill parameters obtained from laboratory tests due to different size effects, which make it necessary to identify parameters from in-situ monitoring data. This paper proposes a novel hybrid back-analysis method with a modified objective function defined for the time-dependent back-analysis problem. The method consists of two stages. In the first stage, an improved weighted average method is proposed to quickly narrow the search region; while in the second stage, an adaptive response surface method is proposed to iteratively search for the satisfactory solution, with a technique that can adaptively consider the translation, contraction or expansion of the exploration region. The accuracy and computational efficiency of the proposed hybrid back-analysis method is demonstrated by back-analyzing the long-term deformation of two high embankments constructed for airport runways, with the rockfills being modeled by a rheological model considering the influence of stress states on the creep behavior.

• Journal of the Korean Data and Information Science Society
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• v.26 no.4
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• pp.907-914
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• 2015

Reduction in the number of students due to the low birth rate has notice very many changes in the national education policies. The purpose of this study is to propose a method for estimation of the number of students (the population) by age or grade promotion rate of progression rate to estimate the exact number of students (the population) by 2032. It was suggested the nth moving average proportional method and the weighted proportional moving average method as the method of population projections. It presents the means and standard deviations of the measurement errors of the suggested methods by Monte Carlo simulation. Measured in this study are predicted result was a phenomenon is estimated lower than the actual value.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.4
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• pp.508-514
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• 2021

In this paper, to propose a classifier based on supervised learning, three types of fuzzy membership functions that determine the membership of each feature of classification data are proposed. In addition, the possibility of improving the classifier performance was suggested by using the average value calculation method used in the process of deriving the classification result using the average value of the membership degrees for each feature, not by using a simple arithmetic average, but by using a weighted average using various weights. To experiment with the proposed methods, three standard data sets were used: Iris, Ecoli, and Yeast. As a result of the experiment, it was confirmed that evenly excellent classification performance can be obtained for data sets of different characteristics. It was confirmed that better classification performance is possible through improvement of fuzzy membership functions and the weighted average methods.

• Journal of Electrical Engineering and Technology
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• v.10 no.4
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• pp.1877-1885
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• 2015

This paper presents a new Nearest-Neighbors based weighted representation for images and weighted K-Nearest-Neighbors (WKNN) classifier to improve the precision of image classification using the Bag of Visual Words (BOVW) based models. Scale-invariant feature transform (SIFT) features are firstly extracted from images. Then, the K-means++ algorithm is adopted in place of the conventional K-means algorithm to generate a more effective visual dictionary. Furthermore, the histogram of visual words becomes more expressive by utilizing the proposed weighted vector quantization (WVQ). Finally, WKNN classifier is applied to enhance the properties of the classification task between images in which similar levels of background noise are present. Average precision and absolute change degree are calculated to assess the classification performance and the stability of K-means++ algorithm, respectively. Experimental results on three diverse datasets: Caltech-101, Caltech-256 and PASCAL VOC 2011 show that the proposed WVQ method and WKNN method further improve the performance of classification.

• 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.

• Korean Journal of Remote Sensing
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• v.28 no.6
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• pp.635-651
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• 2012

To produce a level-3 monthly composite image from daily level-2 Sea-viewing Wide Field-of-view Sensor (SeaWiFS) chlorophyll-a concentration data set in the East Sea, we applied four average methods such as the simple average method, the geometric mean method, the maximum likelihood average method, and the weighted averaging method. Prior to performing each averaging method, we classified all pixels into normal pixels and abnormal speckles with anomalously high chlorophyll-a concentrations to eliminate speckles from the following procedure for composite methods. As a result, all composite maps did not contain the erratic effect of speckles. The geometric mean method tended to underestimate chlorophyll-a concentration values all the time as compared with other methods. The weighted averaging method was quite similar to the simple average method, however, it had a tendency to be overestimated at high-value range of chlorophyll-a concentration. Maximum likelihood method was almost similar to the simple average method by demonstrating small variance and high correlation (r=0.9962) of the differences between the two. However, it still had the disadvantage that it was very sensitive in the presence of speckles within a bin. The geometric mean was most significantly deviated from the remaining methods regardless of the magnitude of chlorophyll-a concentration values. Its bias error tended to be large when the standard deviation within a bin increased with less uniformity. It was more biased when data uniformity became small. All the methods exhibited large errors as chlorophyll-a concentration values dominantly scatter in terms of time and space. This study emphasizes the importance of the speckle removal process and proper selection of average methods to reduce composite errors for diverse scientific applications of satellite-derived chlorophyll-a concentration data.

• Journal of Korea Water Resources Association
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• v.42 no.4
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• pp.297-307
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• 2009

For reliable water quality simulation by semi distributed model, accurate daily runoff simulation should have preceded. In this study, newly developed channel routing method which is nonlinear storage method is combination of Muskingum routing method and variable storage routing method and temporally weighted average curve number method were applied for effect analysis of water quality simulation. Developed modules, which are added in SWAT models and simulation, were conducted for the Chungju dam watershed. The simulation result by each module applied effect. As a result of analysis contribute water quality modeling, nonlinear storage method is more effective than temporally weighted average curve number method. Nutrient loading discharge was affected by development of runoff delaying from improvement of channel routing, because of characteristics of nonpoint source pollution.