• 제목/요약/키워드: Linear Model

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Performance Comparison Analysis of Artificial Intelligence Models for Estimating Remaining Capacity of Lithium-Ion Batteries

  • Kyu-Ha Kim;Byeong-Soo Jung;Sang-Hyun Lee
    • International Journal of Advanced Culture Technology
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    • 제11권3호
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    • pp.310-314
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    • 2023
  • The purpose of this study is to predict the remaining capacity of lithium-ion batteries and evaluate their performance using five artificial intelligence models, including linear regression analysis, decision tree, random forest, neural network, and ensemble model. We is in the study, measured Excel data from the CS2 lithium-ion battery was used, and the prediction accuracy of the model was measured using evaluation indicators such as mean square error, mean absolute error, coefficient of determination, and root mean square error. As a result of this study, the Root Mean Square Error(RMSE) of the linear regression model was 0.045, the decision tree model was 0.038, the random forest model was 0.034, the neural network model was 0.032, and the ensemble model was 0.030. The ensemble model had the best prediction performance, with the neural network model taking second place. The decision tree model and random forest model also performed quite well, and the linear regression model showed poor prediction performance compared to other models. Therefore, through this study, ensemble models and neural network models are most suitable for predicting the remaining capacity of lithium-ion batteries, and decision tree and random forest models also showed good performance. Linear regression models showed relatively poor predictive performance. Therefore, it was concluded that it is appropriate to prioritize ensemble models and neural network models in order to improve the efficiency of battery management and energy systems.

로버스트 선형혼합모형을 이용한 필드시험 데이터 분석 (Analysis of Field Test Data using Robust Linear Mixed-Effects Model)

  • 홍은희;이영조;옥유진;나명환;노맹석;하일도
    • 응용통계연구
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    • 제28권2호
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    • pp.361-369
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    • 2015
  • 연속측도의 반응변수가 반복측정된 실험 자료의 분석을 위해 흔히 선형혼합모형이 사용된다. 그러나, 잔차의 분포가 이분산성이거나 비정규성을 가질 때 표준적인 선형혼합모형은 적절하지 않은 결과를 가져온다. 잔차의 분포가 두터운 꼬리를 가진 비정규분포를 보이는 타이어 필드시험 데이터를 로버스트 선형혼합모형에 적합시킴으로써 보다 더 정확하고 신뢰할 수 있는 분석결과를 얻을 수 있다. 추가적으로 신뢰성 분석 결과를 제시한다.

점탄성 감쇠기의 비선형거동을 고려한 선형모델 해석 (Linear Modeling of Viscoelastic Dampers Considering Nonlinear Dynamic Behavior)

  • 김진구;권영집;민경원
    • 한국구조물진단유지관리공학회 논문집
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    • 제6권1호
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    • pp.171-177
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    • 2002
  • The viscoelastic dampers are considered to be one of the most efficient means of upgrading existing structures against seismic loads. Generally in the dynamic analysis of a structure with added viscoelastic dampers the internal forces of the dampers are represented by constants that are linearly proportional to displacement and velocity. The purpose of this study is to verify the validity of the linear Kelvin model by comparing the results from the linear analysis with those obtained from the more rigorous nonlinear model such as fractional derivative model. According to the results the structural responses of 1-DOF structure obtained using the linear model are very close to those obtained from nonlinear model. However for multi-D0F structure the difference between the results from both models is enlarged as a results of the assumptions associated with the linear modeling of the viscoelastic dampers.

시변 파라메터를 갖는 선형시스템의 균형화된 모델 간략화 (A Balanced Model Reduction for Linear Parameter Varying Systems)

  • 류석환
    • 제어로봇시스템학회논문지
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    • 제8권5호
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    • pp.351-356
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    • 2002
  • This papaer deals with a model reduction problem for linear systems with time varying parameters. For this problem, a controllability Grammian and an observability Grammian are introduced and computed by solving linear matrix inequalities. Using the controllability/observability Grammian, a balanced state space realization for linear parameter varying systems is obtained. From the balanced state space realization, a reduced model can be obtained by truncating not only states but also time varying parameters and an upper bound of the model reduction error is derived as well.

상태변수 시간지연을 갖는 선형시스템의 분수 모델 축소 (A Fractional Model Reduction for Linear Systems with State Delay)

  • Yoo, Seog-Hwan
    • 전자공학회논문지SC
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    • 제41권2호
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    • pp.29-36
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    • 2004
  • 본 논문에서는 시변 시간지연을 갖는 선형시스템의 분수 모델 간략화를 다룬다. 이를 위해 선형 시간지연 시스템의 축소된 소인수 분해를 정의하고 선형 행렬부등식의 해를 이용하여 구한다. 축소된 소인수의 일반화 가제어성, 가관측성 그래미안을 이용하여 시스템의 균형화된 상태공간 모델을 구현한다. 모델 차수축소는 균형화된 상태공간 모델의 일부 상태변수를 절삭하여 얻어지며 모델 오차의 상한치를 제시한다. 제안된 방법의 효용성을 수치 예를 통하여 입증한다.

NEW TREND OF SCHEDULING IN LINEAR CONSTRUCTION PROJECT

  • S. Sankar;J. Senthil
    • 국제학술발표논문집
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    • The 1th International Conference on Construction Engineering and Project Management
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    • pp.917-923
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    • 2005
  • Scheduling is one of the main functions in construction project to determine the sequence of activities necessary to complete a project. The scheduling techniques provide important information crucial to a project's success. Highway construction project the paving activity can be considered a linear activity. Linear scheduling technique may be better suited for linear projects than other scheduling techniques. A new type of scheduling in linear project is calling Linear Scheduling Model (LSM). The Project monitoring and controlling is very ease to identify that all the stage of linear project and have more advantages.

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Hypothesis Testing for New Scores in a Linear Model

  • Park, Young-Hun
    • Communications for Statistical Applications and Methods
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    • 제10권3호
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    • pp.1007-1015
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    • 2003
  • In this paper we introduced a new score generating function for the rank dispersion function in a general linear model. Based on the new score function, we derived the null asymptotic theory of the rank-based hypothesis testing in a linear model. In essence we showed that several rank test statistics, which are primarily focused on our new score generating function and new dispersion function, are mainly distribution free and asymptotically converges to a chi-square distribution.

Bayes Estimation in a Hierarchical Linear Model

  • Park, Kuey-Chung;Chang, In-Hong;Kim, Byung-Hwee
    • Journal of the Korean Statistical Society
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    • 제27권1호
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    • pp.1-10
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    • 1998
  • In the problem of estimating a vector of unknown regression coefficients under the sum of squared error losses in a hierarchical linear model, we propose the hierarchical Bayes estimator of a vector of unknown regression coefficients in a hierarchical linear model, and then prove the admissibility of this estimator using Blyth's (196\51) method.

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에너지 변환 이론에 의한 액추에이터 권선부의 주파수 특성 해석에 관한 연구 (Analysis of the Actuator Winding to a Frequency Characteristic based on Energy Conversion Theory)

  • 김양호;이해경;황석영
    • 조명전기설비학회논문지
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    • 제18권4호
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    • pp.83-87
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    • 2004
  • 본 논문에서는 Magnetic Levitation Model 시스템을 이용하여 선형 액추에이터의 기본모델을 제안하고 전원 공급부의 입력 주파수의 변화로부터 액추에이터에 나타나는 현상을 Matlab프로그램을 활용하여 간접적 방법으로 고찰하였다. 그 결과는 실제적인 설계에 적용할 경우 설계 프로그램의 자료나 부분적 변경 시 참조 할 수 있으리라 사료된다. 본 논문에서 제안한 에너지 변환을 고려한Linear Actuator M3d진 시스템의 출력은 입력 주파수의 변화로부터 액추에이터가 고주파보다는 저주파에서 권선부에 나타나는 파형의 응답이 기준 입력파형에 더 근접함을 알 수 있었다. 이 결과를 바탕으로 Linear Actuator Model 시스템의 동작 시 특성이 실제 시스템에 활용할 때 간접적 방법으로 상당히 유용함을 확인 할 수 있었다.

DCS Model Calculation for Steam Temperature System

  • Hwang, Jae-Ho
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2004년도 ICCAS
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    • pp.1201-1204
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    • 2004
  • This paper suggests a DCS (Distributed Control System) model for steam temperature system of the thermal power plant. The model calculated within sectional range is linear. In order to calculate mathematical models, the system is partitioned into two or three sectors according to its thermal conditions, that is, saturated water/steam and superheating state. It is divided into three sections; water supply, steam generation and steam heating loop. The steam heating loop is called 'superheater' or steam temperature system. Water spray supply is the control input. A first order linear model is extracted. For linear approach, sectional linearization is achieved. Modeling methodology is a decomposition-synthetic technique. Superheater is composed of several tube-blocks. For this block, linear input-output model is to be calculated. Each tiny model has its transfer function. By expanding these block models to total system, synthetic DCS linear models are derived. Control instrument include/exclude models are also considered. The resultant models include thermal combustion conditions, and applicable to practical plant engineering field.

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