• Title/Summary/Keyword: mean functions comparison

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Comparison of Objective Functions for Feed-forward Neural Network Classifiers Using Receiver Operating Characteristics Graph

  • Oh, Sang-Hoon;Wakuya, Hiroshi
    • International Journal of Contents
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    • v.10 no.1
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    • pp.23-28
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    • 2014
  • When developing a classifier using various objective functions, it is important to compare the performances of the classifiers. Although there are statistical analyses of objective functions for classifiers, simulation results can provide us with direct comparison results and in this case, a comparison criterion is considerably critical. A Receiver Operating Characteristics (ROC) graph is a simulation technique for comparing classifiers and selecting a better one based on a performance. In this paper, we adopt the ROC graph to compare classifiers trained by mean-squared error, cross-entropy error, classification figure of merit, and the n-th order extension of cross-entropy error functions. After the training of feed-forward neural networks using the CEDAR database, the ROC graphs are plotted to help us identify which objective function is better.

Nonparametric Change-point Estimation with Rank and Mean Functions in a Location Parameter Change Model (위치모수 변화 모형에서 순위함수와 평균함수를 이용한 비모수적 변화점 추정)

  • Kim, Jae-Hee;Lee, Kyoung-Won
    • Journal of the Korean Data and Information Science Society
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    • v.11 no.2
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    • pp.279-293
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    • 2000
  • This article suggests two change-point estimators which are modifications of Carlstein(1988) change-point estimators with rank functions and mean functions where there is one change-point in a mean function. A comparison study of Carlstein(1988) estimators and proposed estimators is done by simulation on the mean, the MSE, and the proportion of matching true change-point.

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Comparison of Probability Density Functions for Caculation of Capacity Factors of Wind Turbine Generator (풍력발전기의 설비이용률 계산을 위한 확률밀도함수의 비교)

  • Kang, Taeg-Geun;Huh, Jong-Chul;Jwa, Chong-Keun
    • Proceedings of the KIEE Conference
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    • 2002.07b
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    • pp.1338-1341
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    • 2002
  • The Weibull probability density function and the Rayleigh function are compared by analyzing the relations of the capacity factors which are compared the actual wind speed frequency curve with which are modelled using the probability density functions with different mean wind speeds. For this analysis, the wind speed means of arithmetic, root mean square, cubic mean cuberoot, and standard deviations are computed from the measured wind speed data of a specific site and the coefficients of probability density functions are calculated. The capacity factors for Vestas 850[kW] wind turbine are calculated and analyzed. The results shows that the wind speed frequency curve by Rayleigh function is more close to the actual curve than by Weibull function. The more the wind speed frequency curve is close to the actual one, the more the capacity factors become large values.

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Bayesian Inferences for Software Reliability Models Based on Beta-Mixture Mean Value Functions

  • Nam, Seung-Min;Kim, Ki-Woong;Cho, Sin-Sup;Yeo, In-Kwon
    • The Korean Journal of Applied Statistics
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    • v.21 no.5
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    • pp.835-843
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    • 2008
  • In this paper, we investigate a Bayesian inference for software reliability models based on mean value functions which take the form of the mixture of beta distribution functions. The posterior simulation via the Markov chain Monte Carlo approach is used to produce estimates of posterior properties. Its applicability is illustrated with two real data sets. We compute the predictive distribution and the marginal likelihood of various models to compare the performance of them. The model comparison results show that the model based on the beta-mixture performs better than other models.

A Two Sample Test for Functional Data

  • Lee, Jong Soo;Cox, Dennis D.;Follen, Michele
    • Communications for Statistical Applications and Methods
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    • v.22 no.2
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    • pp.121-135
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    • 2015
  • We consider testing equality of mean functions from two samples of functional data. A novel test based on the adaptive Neyman methodology applied to the Hotelling's T-squared statistic is proposed. Under the enlarged null hypothesis that the distributions of the two populations are the same, randomization methods are proposed to find a null distribution which gives accurate significance levels. An extensive simulation study is presented which shows that the proposed test works very well in comparison with several other methods under a variety of alternatives and is one of the best methods for all alternatives, whereas the other methods all show weak power at some alternatives. An application to a real-world data set demonstrates the applicability of the method.

Performance comparison evaluation of speech enhancement using various loss functions (다양한 손실 함수를 이용한 음성 향상 성능 비교 평가)

  • Hwang, Seo-Rim;Byun, Joon;Park, Young-Cheol
    • The Journal of the Acoustical Society of Korea
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    • v.40 no.2
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    • pp.176-182
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    • 2021
  • This paper evaluates and compares the performance of the Deep Nerual Network (DNN)-based speech enhancement models according to various loss functions. We used a complex network that can consider the phase information of speech as a baseline model. As the loss function, we consider two types of basic loss functions; the Mean Squared Error (MSE) and the Scale-Invariant Source-to-Noise Ratio (SI-SNR), and two types of perceptual-based loss functions, including the Perceptual Metric for Speech Quality Evaluation (PMSQE) and the Log Mel Spectra (LMS). The performance comparison was performed through objective evaluation and listening tests with outputs obtained using various combinations of the loss functions. Test results show that when a perceptual-based loss function was combined with MSE or SI-SNR, the overall performance is improved, and the perceptual-based loss functions, even exhibiting lower objective scores showed better performance in the listening test.

Comparison of CME mean density based on a full ice-cream cone structure and its corresponding ICME one

  • Na, Hyeonock;Moon, Yong-Jae
    • The Bulletin of The Korean Astronomical Society
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    • v.43 no.1
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    • pp.54.1-54.1
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    • 2018
  • For space weather forecast, it is important to determine three-dimensional parameters of coronal mass ejections (CMEs). To estimate three-dimensional parameters of CMEs, we have developed a full ice-cream cone model which is a combination of a symmetrical flat cone and a hemisphere. By applying this model to 12 SOHO/LASCO halo CMEs, we find that three-dimensional parameters from our method are similar to those from other stereoscopic methods. For several geoeffective CME events, we determine CME mass by applying the Solarsoft procedure (e.g., cme_mass.pro) to SOHO/LASCO C3 images. CME volumes are estimated from the full ice-cream cone structure. We derive CME mean density as a function of CME height for these CMEs, which are approximately fitted to power-law functions. We find that the ICME mean densities extrapolated from the power law functions, are correlated with their corresponding ICME ones in logarithmic scales.

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Comparison of Change-point Estimators with Scores

  • Kim, Jae-Hee;Seo, Hyun-Joo
    • Journal of the Korean Data and Information Science Society
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    • v.13 no.1
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    • pp.165-175
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    • 2002
  • We consider the problem of estimating the change-point in mean change model with the one change-point. Lombard (1987) suggested change-point estimation based on score functions. Gombay and Huskova (1998) derived a class of change-point estimators with the score function of rank. Various change-point estimators with the log score functions of ranks are suggested and compared via simulation.

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Comparison of Automatic Calibration for a Tank Model with Optimization Methods and Objective Functions

  • Kang, Min-Goo;Park, Seung-Woo;Park, Chang-Eun
    • Magazine of the Korean Society of Agricultural Engineers
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    • v.44 no.7
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    • pp.1-13
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    • 2002
  • Two global optimization methods, the SCE-UA method and the Annealing-simplex (A-S) method for calibrating a daily rainfall-runoff model, a Tank model, was compared with that of the Downhill Simplex method. The performance of the four objective functions, DRMS (daily root mean square), HMLE (heteroscedastic maximum likelihood estimator), ABSERR (mean absolute error), and NS (Nash-Sutcliffe measure), was tested and synthetic data and historical data were used. In synthetic data study. 100% success rates for all objective functions were obtained from the A-S method, and the SCE-UA method was also consistently able to obtain good estimates. The downhill simplex method was unable to escape from local optimum, the worst among the methods, and converged to the true values only when the initial guess was close to the true values. In the historical data study, the A-S method and the SCE-UA method showed consistently good results regardless of objective function. An objective function was developed with combination of DRMS and NS, which putted more weight on the low flows.

Temperature Effect on the Configurational Properties of an n-Decane Chain in Solution

  • Oh, In-Joon;Ree, Tai-Kyue
    • Bulletin of the Korean Chemical Society
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    • v.5 no.4
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    • pp.162-167
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    • 1984
  • Equilibrium and dynamical behaviors of an n-alkane poymer (decane) in solution have been investigated by a molecuar dynamics simulation method. The polymer is assumed to be a chain of elements $(CH_2)$ interconnected by bonds having a fixed bond length and bond angle, but esch bond of the polymer is allowed to execute hindered internal rotation. The calculation explicitly considers the molecular naturer of solvent by including the intermolecular interactions between slovent-solvent molecules and chain element-solvent molecule. We present the results of calculations on (1) equilibrium properties (the solvent molecule-chain element pair correlation function, chain element-chain element pair correlation function, the mean square end-to-end distance and the mean square radius of gyration of the polymer) and (2) dynamic properties (four different autocorrelation functions, namely, the autocorrelation functions for the end-to-end distance and the radius of gyration, and the velocity autocorrelation functions for the center of mass and the end point of the chain). We found that the physical properties of the polymer chain depends sensitively on temperature. Comparison of the present work with other authors' results is also presented.