• 제목/요약/키워드: Correlation model

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Model- Data Based Small Area Estimation

  • Shin, Key-Il;Lee, Sang Eun
    • Communications for Statistical Applications and Methods
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    • 제10권3호
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    • pp.637-645
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    • 2003
  • Small area estimation had been studied using data-based methods such as Direct, Indirect, Synthetic methods. However recently, model-based such as based on regression or time series estimation methods are applied to the study. In this paper we investigate a model-data based small area estimation which takes into account the spatial relation among the areas. The Economic Active Population Survey in 2001 are used for analysis and the results from the model based and model-data based estimation are compared with using MSE(Mean squared error), MAE(Mean absolute error) and MB(Mean bias).

성층화 혼합기의 연소 모델링 (Combustion Modeling for Stratified Charge)

  • 김용태;배상수;민경덕
    • 한국자동차공학회논문집
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    • 제9권4호
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    • pp.50-55
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    • 2001
  • To simulate the combustion process under stratified charged conditions, like GDI engines, the new combustion model is proposed, which is based on Welter's FAE model and Peters' PDF model for considering primary reactions. In addition to these models, the new laminar burning velocity correlation and diffusion flame model are also included in the proposed model. The former can be applicable to much wider range of equivalence ratio, pressure and temperature than the others, such as Keck's and Guilder's models, and the latter has been derived from water-gas shift reaction and hydrogen oxidation, by which the secondary reactions can be considered after primary reactions. 3-D computation has been performed by using STAR-CD v3.05 in the simple cylindrical geometry under stratified charged condition. Judging from the calculated results, the present model proves to be reasonable to simulate the characteristics of flame propagation and concentrations of products in burned regions.

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의복 쇼핑 성향의 개념적 구조 규명 (Development of Conceptual Structure for Clothing Shopping Orientation)

  • 김세희;이은영
    • 한국의류학회지
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    • 제28권6호
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    • pp.830-841
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    • 2004
  • The necessity to understand shopping orientation is increasing. Yet, there has been few research that investigated the conceptual structure of clothing shopping orientation[CSO]. Therefore, the purpose of this study is to develop the conceptual structure of CSO. For that purpose, both documentary and empirical researches were conducted. The documentary research was conducted to develop a theoretical structure model as a basis for exploring the conceptual structure of CSO. The empirical research was conducted to identify and modify the theoretical model so as to develop a conceptual structure model. The data was analyzed using confirmatory factor analysis, exploratory factor analysis, and Pearson's correlation analysis. As a result, a conceptual structure model of CSO was developed. The model consisted of three hierarchical levels of dimensions; upper-dimensions, middle-dimensions and lower-dimensions. The upper-dimensions were composed of 'economic', 'hedonic', and 'convenient' dimensions. Each upper-dimension consisted of middle-dimensions and lower-dimensions. Confirmatory factor analysis was executed to assess the fitness and cross validity of the structure model.

용담호 수온성층해석을 위한 유입수온 회귀분석 모형 개발 (Development of the Inflow Temperature Regression Model for the Thermal Stratification Analysis in Yongdam Reservoir)

  • 안기홍;김선주;서동일
    • 환경영향평가
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    • 제20권4호
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    • pp.435-442
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    • 2011
  • In this study, a regression model was developed for prediction of inflow temperature to support an effective thermal stratification simulation of Yongdam Reservoir, using the relationship between gaged inflow temperature and air temperature. The effect of reproductability for thermal stratification was evaluated using EFDC model by gaged vertical profile data of water temperature(from June to December in 2005) and ex-developed regression models. Therefore, in the development process, the coefficient of correlation and determination are 0.96 and 0.922, respectively. Moreover, the developed model showed good performance in reproducing the reservoir thermal stratification. Results of this research can be a role to provide a base for building of prediction model for water quality management in near future.

품질기능전개를 이용한 자본투자프로젝트 선정방법 (A Selection Method for Capital Budgeting Projects with Quality Function Deployment)

  • 우태희
    • 대한안전경영과학회:학술대회논문집
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    • 대한안전경영과학회 2000년도 추계학술발표논문집
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    • pp.81-85
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    • 2000
  • The purpose of this paper is to describe a new analytic method of capital budgeting projects that takes into account both customer wants and competitor's status and to give decision makers a tool for goal setting and planning for technology. This model, which is based on quality function deployment(QFD), has used the analytic hierarchy process(AHP) to determine the intensity of the relationship between the variables involved in each matrix of the model and the 0-1 integer programming to determine the allocation of funds to various technological projects. This paper also proposes how to calculate the new weight of columns to consider various strength levels of roof matrix, representing the correlation among the quality characteristics, using Lymsn's normalization procedure. To compare this model with Partovi's model, 1 adapt the same example which is suggested by Partovi and I show that the value of object function, has maximization problem, in this model is larger than that in Partovi's model.

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A Neoteric Three-Dimensional Geometry-Based Stochastic Model for Massive MIMO Fading Channels in Subway Tunnels

  • Jiang, Yukang;Guo, Aihuang;Zou, Jinbai;Ai, Bo
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제13권6호
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    • pp.2893-2907
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    • 2019
  • Wireless mobile communication systems in subway tunnels have been widely researched these years, due to increased demand for the communication applications. As a result, an accurate model is essential to effectively evaluate the communication system performance. Thus, a neoteric three-dimensional (3D) geometry-based stochastic model (GBSM) is proposed for the massive multiple-input multiple-output (MIMO) fading channels in tunnel environment. Furthermore, the statistical properties of the channel such as space-time correlation, amplitude and phase probability density are analyzed and compared with those of the traditional two-dimensional (2D) model by numerical simulations. Finally, the ergodic capacity is investigated based on the proposed model. Numerical results show that the proposed model can describe the channel in tunnels more practically.

Information Dissemination Model of Microblogging with Internet Marketers

  • Xu, Dongliang;Pan, Jingchang;Wang, Bailing;Liu, Meng;Kang, Qinma
    • Journal of Information Processing Systems
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    • 제15권4호
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    • pp.853-864
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    • 2019
  • Microblogging services (such as Twitter) are the representative information communication networks during the Web 2.0 era, which have gained remarkable popularity. Weibo has become a popular platform for information dissemination in online social networks due to its large number of users. In this study, a microblog information dissemination model is presented. Related concepts are introduced and analyzed based on the dynamic model of infectious disease, and new influencing factors are proposed to improve the susceptible-infective-removal (SIR) information dissemination model. Correlation analysis is conducted on the existing information dissemination risk and the rumor dissemination model of microblog. In this study, web hyper is used to model rumor dissemination. Finally, the experimental results illustrate the effectiveness of the method in reducing the rumor dissemination of microblogs.

A Federated Multi-Task Learning Model Based on Adaptive Distributed Data Latent Correlation Analysis

  • Wu, Shengbin;Wang, Yibai
    • Journal of Information Processing Systems
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    • 제17권3호
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    • pp.441-452
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    • 2021
  • Federated learning provides an efficient integrated model for distributed data, allowing the local training of different data. Meanwhile, the goal of multi-task learning is to simultaneously establish models for multiple related tasks, and to obtain the underlying main structure. However, traditional federated multi-task learning models not only have strict requirements for the data distribution, but also demand large amounts of calculation and have slow convergence, which hindered their promotion in many fields. In our work, we apply the rank constraint on weight vectors of the multi-task learning model to adaptively adjust the task's similarity learning, according to the distribution of federal node data. The proposed model has a general framework for solving optimal solutions, which can be used to deal with various data types. Experiments show that our model has achieved the best results in different dataset. Notably, our model can still obtain stable results in datasets with large distribution differences. In addition, compared with traditional federated multi-task learning models, our algorithm is able to converge on a local optimal solution within limited training iterations.

A Bayesian joint model for continuous and zero-inflated count data in developmental toxicity studies

  • Hwang, Beom Seuk
    • Communications for Statistical Applications and Methods
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    • 제29권2호
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    • pp.239-250
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    • 2022
  • In many applications, we frequently encounter correlated multiple outcomes measured on the same subject. Joint modeling of such multiple outcomes can improve efficiency of inference compared to independent modeling. For instance, in developmental toxicity studies, fetal weight and number of malformed pups are measured on the pregnant dams exposed to different levels of a toxic substance, in which the association between such outcomes should be taken into account in the model. The number of malformations may possibly have many zeros, which should be analyzed via zero-inflated count models. Motivated by applications in developmental toxicity studies, we propose a Bayesian joint modeling framework for continuous and count outcomes with excess zeros. In our model, zero-inflated Poisson (ZIP) regression model would be used to describe count data, and a subject-specific random effects would account for the correlation across the two outcomes. We implement a Bayesian approach using MCMC procedure with data augmentation method and adaptive rejection sampling. We apply our proposed model to dose-response analysis in a developmental toxicity study to estimate the benchmark dose in a risk assessment.

Lyapunov 차원을 이용한 화자식별 파라미터 추정 (Estimation of Speeker Recognition Parameter using Lyapunov Dimension)

  • 유병욱;김창석
    • 한국음향학회지
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    • 제16권4호
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    • pp.42-48
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    • 1997
  • 본 논문에서는 음성을 비선형 결정론적 발생메카니즘에서 발생되는 불규칙한 신호인 카오스로 보고 상관차원과 Lyapunov 차원을 구함으로써 음성화자식별 파라미터와 음성인식파라미터에 대한 성능을 평가하였다. Taken의 매립정리를 이용하여 스트레인지 어트렉터를 구성할 때 AR모델의 파워스펙트럼으로부터 주요주기를 구함으로써 정확한 상관차원과 Lyapunov 차원을 추정하였다. 이트렉터 궤도의 특징을 잘 나타내는 상관차원과 Lyapunov 차원을 가지고 음성인식과 화자인식의 특징파라미터로의 효용성을 고찰하였다. 그 결과, 음성인식보다는 화자식별의 특징파라미터로타당하였으며 화자식별 특징파라미터로서는 상관차원보다는 Lyapunov 차원이 높은 화자식별 인식율을 얻을 수 있음을 알았다.

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