• Title/Summary/Keyword: Linear models

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Utterance Verification Using Anti-models Based on Neighborhood Information (이웃 정보에 기초한 반모델을 이용한 발화 검증)

  • Yun, Young-Sun
    • MALSORI
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    • no.67
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    • pp.79-102
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    • 2008
  • In this paper, we investigate the relation between Bayes factor and likelihood ratio test (LRT) approaches and apply the neighborhood information of Bayes factor to building an alternate hypothesis model of the LRT system. To consider the neighborhood approaches, we contemplate a distance measure between models and algorithms to be applied. We also evaluate several methods to improve performance of utterance verification using neighborhood information. Among these methods, the system which adopts anti-models built by collecting mixtures of neighborhood models obtains maximum error rate reduction of 17% compared to the baseline, linear and weighted combination of neighborhood models.

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The Change Point Analysis in Time Series Models

  • Lee, Sang-Yeol
    • Proceedings of the Korean Statistical Society Conference
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    • 2005.11a
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    • pp.43-48
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    • 2005
  • We consider the problem of testing for parameter changes in time series models based on a cusum test. Although the test procedure is well-established for the mean and variance in time series models, a general parameter case has not been discussed in the literature. Therefore, here we develop a cusum test for parameter change in a more general framework. As an example, we consider the change of the parameters in an RCA(1) model and that of the autocovariances of a linear process. We also consider the variance change test for unstable models with unit roots and GARCH models.

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Accuracy and precision of polyurethane dental arch models fabricated using a three-dimensional subtractive rapid prototyping method with an intraoral scanning technique

  • Kim, Jae-Hong;Kim, Ki-Baek;Kim, Woong-Chul;Kim, Ji-Hwan;Kim, Hae-Young
    • The korean journal of orthodontics
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    • v.44 no.2
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    • pp.69-76
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    • 2014
  • Objective: This study aimed to evaluate the accuracy and precision of polyurethane (PUT) dental arch models fabricated using a three-dimensional (3D) subtractive rapid prototyping (RP) method with an intraoral scanning technique by comparing linear measurements obtained from PUT models and conventional plaster models. Methods: Ten plaster models were duplicated using a selected standard master model and conventional impression, and 10 PUT models were duplicated using the 3D subtractive RP technique with an oral scanner. Six linear measurements were evaluated in terms of x, y, and z-axes using a non-contact white light scanner. Accuracy was assessed using mean differences between two measurements, and precision was examined using four quantitative methods and the Bland-Altman graphical method. Repeatability was evaluated in terms of intra-examiner variability, and reproducibility was assessed in terms of interexaminer and inter-method variability. Results: The mean difference between plaster models and PUT models ranged from 0.07 mm to 0.33 mm. Relative measurement errors ranged from 2.2% to 7.6% and intraclass correlation coefficients ranged from 0.93 to 0.96, when comparing plaster models and PUT models. The Bland-Altman plot showed good agreement. Conclusions: The accuracy and precision of PUT dental models for evaluating the performance of oral scanner and subtractive RP technology was acceptable. Because of the recent improvements in block material and computerized numeric control milling machines, the subtractive RP method may be a good choice for dental arch models.

Hydrologic Re-Analysis of Muskingum Channel Routing Method: A Linear Combination of Linear Reservoir and Linear Channel Models (Muskingum 하도추적방법의 수문학적 재해석: 선형저수지모형과 선형하천모형의 선형결합)

  • Yoo, Chul-Sang;Kim, Ha-Young
    • Journal of Korea Water Resources Association
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    • v.43 no.12
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    • pp.1051-1061
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    • 2010
  • This study hydrologically re-analysed the Muskingum channel routing method to represent it as a linear combination of the linear channel model considering only the translation and the linear reservoir model considering only the storage effect. The resulting model becomes a kind of instantaneous unit hydrograph, whose parameters are identical to those of the Muskingum model. That is, the outflow occurs after the routing interval ${\Delta}t$ or concentration time $T_c$, and among the total amount of inflow, the x portion is translated by the linear channel model and the remaining (1-x) portion is routed by the linear reservoir model with the storage coefficient ��$K_c$. The application result of both the Muskingum channel routing method and its corresponding instantaneous unit hydrograph to an imaginary channel showed that these two models are basically identical. This result was also assured by the application to the channel flood routing to the Kumnam and Gongju Station for the discharge from the Daechung Dam.

A Review for Non-linear Models Describing Temperature-dependent Development of Insect Populations: Characteristics and Developmental Process of Models (비선형 곤충 온도발육모형의 특성과 발전과정에 대한 고찰)

  • Kim, Dong-Soon;Ahn, Jeong Joon;Lee, Joon-Ho
    • Korean journal of applied entomology
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    • v.56 no.1
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    • pp.1-18
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    • 2017
  • Temperature-dependent development model is an essential component for forecasting models of insect pests as well as for insect population models. This study reviewed the nonlinear models which explain the relationship between temperature and development rate of insects. In the present study, the types of models were classified largely into empirical and biophysical model, and the groups were subdivided into subgroups according to the similarity of mathematical equations or the connection with original idea. Empirical models that apply analytical functions describing the suitable shape of development curve were subdivided into multiple subgroups as Stinner-based types, Logan-based types, performance models and Beta distribution types. Biophysical models based on enzyme kinetic reaction were grouped as monophyletic group leading to Eyring-model, SM-model, SS-mode, and SSI-model. Finally, we described the historical development and characteristics of non-linear development models and discussed the availability of models.

A comparison of formulas to predict a team's winning percentage in Korean pro-baseball (한국프로야구에서 승률 추정방법들의 비교)

  • Lee, Jang Taek
    • Journal of the Korean Data and Information Science Society
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    • v.27 no.6
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    • pp.1585-1592
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    • 2016
  • Estimation of winning percentage in baseball has always been particularly interesting to many baseball fans. We have fitted models including linear regression and Pythagorean formula to the Korean baseball data of seasons from 1982 to 2015. Using RMSE criterion for both the linear formula and the Pythagorean formula, we compared two models in predicting the actual winning percentage. Pythagorean expectation is superior to linear formula when there is either high or low winning percentage. Two methods yield very similar efficiencies when the actual winning percentage is about 50%. To understand and use for estimating winning percentage, it is easier linear formula as estimated equations.

Various Models of Fuzzy Least-Squares Linear Regression for Load Forecasting (전력수요예측을 위한 다양한 퍼지 최소자승 선형회귀 모델)

  • Song, Kyung-Bin
    • Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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    • v.21 no.7
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    • pp.61-67
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    • 2007
  • The load forecasting has been an important part of power system Accordingly, it has been proposed various methods for the load forecasting. The load patterns of the special days is quite different than those of ordinary weekdays. It is difficult to accurately forecast the load of special days due to the insufficiency of the load patterns compared with ordinary weekdays, so we have proposed fuzzy least squares linear regression algorithm for the load forecasting. In this paper we proposed four models for fuzzy least squares linear regression. It is separated by coefficients of fuzzy least squares linear regression equation. we compared model of H1 with H4 and prove it H4 has accurately forecast better than H1.

Nonlinear damage detection using linear ARMA models with classification algorithms

  • Chen, Liujie;Yu, Ling;Fu, Jiyang;Ng, Ching-Tai
    • Smart Structures and Systems
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    • v.26 no.1
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    • pp.23-33
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    • 2020
  • Majority of the damage in engineering structures is nonlinear. Damage sensitive features (DSFs) extracted by traditional methods from linear time series models cannot effectively handle nonlinearity induced by structural damage. A new DSF is proposed based on vector space cosine similarity (VSCS), which combines K-means cluster analysis and Bayesian discrimination to detect nonlinear structural damage. A reference autoregressive moving average (ARMA) model is built based on measured acceleration data. This study first considers an existing DSF, residual standard deviation (RSD). The DSF is further advanced using the VSCS, and then the advanced VSCS is classified using K-means cluster analysis and Bayes discriminant analysis, respectively. The performance of the proposed approach is then verified using experimental data from a three-story shear building structure, and compared with the results of existing RSD. It is demonstrated that combining the linear ARMA model and the advanced VSCS, with cluster analysis and Bayes discriminant analysis, respectively, is an effective approach for detection of nonlinear damage. This approach improves the reliability and accuracy of the nonlinear damage detection using the linear model and significantly reduces the computational cost. The results indicate that the proposed approach is potential to be a promising damage detection technique.

The Research about Free Piston Linear Engine Fueled with Hydrogen using Numerical Analysis (수소를 연료로 사용한 프리피스톤 리니어 엔진의 수치해석에 관한 연구)

  • Nguyen, Ba Hung;Oh, Yong-Il;Lim, Ock-Taeck
    • Transactions of the Korean hydrogen and new energy society
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    • v.23 no.2
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    • pp.162-172
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    • 2012
  • This paper presents a research about free piston linear engine (FPLE) fueled with hydrogen, in which, the numerical models are built to simulate the operation during the full stroke of the engine. Dynamic model, linear alternator model and thermodynamic model are used as the numerical models to predict piston velocity, in-cylinder pressure and electric power of FPLE. The spark timing and air gap length are changed to provide information for the prediction. Beside, the heat transfer problem is also investigated in the paper. The results of research are divided by two parts, including motoring mode and firing mode. The result of motoring mode showed that there is validation between simulation and experiment for volume and pressure in cylinder. For firing mode, by increasing spark timing, the velocity of piston, peak pressure and electric power also increase respectively. Beside, when increasing air gap length, the electric power increases accordingly while the motion of piston is not symmetric. The effect of heat transfer also observed clearly by reducing of the peak pressure, velocity of piston and electric power.

Variable selection in partial linear regression using the least angle regression (부분선형모형에서 LARS를 이용한 변수선택)

  • Seo, Han Son;Yoon, Min;Lee, Hakbae
    • The Korean Journal of Applied Statistics
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    • v.34 no.6
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    • pp.937-944
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    • 2021
  • The problem of selecting variables is addressed in partial linear regression. Model selection for partial linear models is not easy since it involves nonparametric estimation such as smoothing parameter selection and estimation for linear explanatory variables. In this work, several approaches for variable selection are proposed using a fast forward selection algorithm, least angle regression (LARS). The proposed procedures use t-test, all possible regressions comparisons or stepwise selection process with variables selected by LARS. An example based on real data and a simulation study on the performance of the suggested procedures are presented.