• 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.

• Journal of the Korean Data and Information Science Society
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• 제17권1호
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• pp.123-130
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• 2006

This paper discusses about how to build up a mixed-effects model using cumulative logits when some factors are fixed and others are random. Location effects are considered as random effects by choosing them randomly from a population of locations. Estimation procedure for the unknown parameters in a suggested model is also discussed by an illustrated example.

• 한국수자원학회논문집
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• 제32권1호
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• pp.61-70
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• 1999

자연하천에 유입된 오염물질의 확산거동을 해석하기 위하여 통계학적인 개념을 이용하여 오염물질 입자의 운동을 묘사하는 2차원 Random-Walk 모형을 개발하였다. 개발된 모형을 검정한 결과, 고정격자의 개수를 증가시키거나 각각의 고정격자 내에 포함된 입자개수의 평균값을 증가시키면 해의 정밀도가 증가하는 것으로 나타났다. 본 모형의 현장 적용성을 검토하기 위하여 캐나다에 위치한 Grand River에서 수행된 정상상태의 색소실험 결과와 본 모형에 의한 계산결과를 비교하였다. 그 결과 본 모형은 단면과 곡률이 불규칙하게 변하는 자연하천에서의 횡확산을 정확하게 모의하는 것으로 나타났다.

• 한국경영과학회지
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• 제22권1호
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• pp.51-58
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• 1997

In this paper, we propose a stochastic LP model for determining an optimal input quantity in a single-product multi-stage production system with random yields. Due to the random yields in our model, each stage of the production system can result in defective items, which can be re-processed or scrapped at certain costs. We assume that the random yield at each stage follows an independent discrete empirical distribution. Compared to dynamic programming models that prevail in the literature, our model can easily handle problems of larger sizes.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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• pp.1722-1725
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• 1997

This paper presents image analysis method using a Markov random field(MRF) model. Particulary, image esgmentation is to partition the given image into regions. This scheme is first segmented into regions, and the obtained domain knowledge is used to obtain the improved segmented image by a Markov random field model. The method is a maximum a posteriori(MAP) estimation with the MRF model and its associated Gibbs distribution. MAP estimation method is applied to capture the natural image by TMS320C80(MVP) and to realize the segmented image by a MRF model.

• Communications for Statistical Applications and Methods
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• 제25권3호
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• pp.275-282
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• 2018

This paper discusses the use of projections for the sums of squares in the analyses of variance for two-way nested design data. The model for this data is assumed to only have random effects. Two different sizes of experimental units are required for a given experimental situation, since nesting is assumed to occur both in the treatment structure and in the design structure. So, variance components are coming from the sources of random effects of treatment factors and error terms in different sizes of experimental units. The model for this type of experimental situation is a random effects model with more than one error terms and therefore estimation of variance components are concerned. A projection method is used for the calculation of sums of squares due to random components. Squared distances of projections instead of using the usual reductions in sums of squares that show how to use projections to estimate the variance components associated with the random components in the assumed model. Expectations of quadratic forms are obtained by the Hartley's synthesis as a means of calculation.

• 한국도로학회논문집
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• 제17권6호
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• pp.65-73
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• 2015

PURPOSES : This study tries to develop the accident models of 4-legged signalized intersections in Busan Metropolitan city with random parameter in count model to understanding the factors mainly influencing on accident frequencies. METHODS : To develop the traffic accidents modeling, this study uses RP(random parameter) negative binomial model which enables to take account of heterogeneity in data. By using RP model, each intersection's specific geometry characteristics were considered. RESULTS : By comparing the both FP(fixed parameter) and RP modeling, it was confirmed the RP model has a little higher explanation power than the FP model. Out of 17 statistically significant variables, 4 variables including traffic volumes on minor roads, pedestrian crossing on major roads, and distance of pedestrian crossing on major/minor roads are derived as having random parameters. In addition, the marginal effect and elasticity of variables are analyzed to understand the variables'impact on the likelihood of accident occurrences. CONCLUSIONS : This study shows that the uses of RP is better fitted to the accident data since each observations'specific characteristics could be considered. Thus, the methods which could consider the heterogeneity of data is recommended to analyze the relationship between accidents and affecting factors(for example, traffic safety facilities or geometrics in signalized 4-legged intersections).

• Wind and Structures
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• 제36권2호
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• pp.133-147
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• 2023

The random vibration of saddle membrane structures under wind load is studied theoretically and experimentally. First, the nonlinear random vibration differential equations of saddle membrane structures under wind loads are established based on von Karman's large deflection theory, thin shell theory and potential flow theory. The probabilistic density function (PDF) and its corresponding statistical parameters of the displacement response of membrane structure are obtained by using the diffusion process theory and the Fokker Planck Kolmogorov equation method (FPK) to solve the equation. Furthermore, a wind tunnel test is carried out to obtain the displacement time history data of the test model under wind load, and the statistical characteristics of the displacement time history of the prototype model are obtained by similarity theory and probability statistics method. Finally, the rationality of the theoretical model is verified by comparing the experimental model with the theoretical model. The results show that the theoretical model agrees with the experimental model, and the random vibration response can be effectively reduced by increasing the initial pretension force and the rise-span ratio within a certain range. The research methods can provide a theoretical reference for the random vibration of the membrane structure, and also be the foundation of structural reliability of membrane structure based on wind-induced response.

• 무역학회지
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• 제41권3호
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• pp.177-198
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• 2016

중국은 1979년부터 본격적으로 시장경제체제를 도입함으로써 급격한 경제성장을 이루었는데, 본고는 저임금과 중국정부의 적극적인 외자유치정책을 활용하기 위해 밀려들어온 외국인투자에 어떤 요인들이 영향을 미쳤는지를 검토하기 위해 1979년부터 2013년까지의 패널데이터를 이용해서 각 성·시의 고유한 특성까지 활용하는 실증분석을 시도한다. 실증분석을 위해 본고는 확률효과모형, 고정효과모형, Pooled OLS, 그리고 확률계수모형을 사용하는데, Pooled OLS와 확률계수모형의 결과는 본 연구의 분석결과와 비교를 위해서 제시된다. Hausman' test 결과 Random Effect Model보다는 Fixed Effect Model이 더 효율적인 분석결과를 제시하는 것으로 나타나 이를 근거로 중국정부에 대한 정책적 시사점을 제시한다. 분석결과는 FDI유입에 각 성·시의 지역소득수준, 자본량, 통신비는 긍정적인 영향을 미치고 고속도로는 부정적인 영향을 미치는 것으로 나타난다.

• 응용통계연구
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• 제28권6호
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• pp.1121-1131
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• 2015

의학이나 사회과학에서 이진 데이터 분석 시 랜덤 절편(random intercept)을 갖는 로지스틱 모형이 유용하게 쓰이고 있다. 지금까지는 이러한 로지스틱 모형에서 랜덤 절편이 정규분포와 같은 모수 모형(parametric model)을 따른다는 가정과 설명변수와 랜덤 절편이 독립이라는 가정 하에 실행된 데이터 분석이 전반적이었다. 그러나 이러한 두 가지 가정은 다소 무리가 있다. 이 연구에서는 설명 변수와 랜덤 절편의 독립성을 가정하지 않고, 비모수 랜덤 절편을 따르는 로지스틱 모형의 방법론을 기존에 널리 쓰인 방법과 비교하여 설명하도록 한다. 케냐의 초등학생들의 영양 섭취 및 질병의 발병을 조사한 데이터에 이 방법을 적용하였다.