• Title/Summary/Keyword: Mixed approach

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Design of a navigation system using GPS and dead-reckoning (GPS와 dead-reckoning을 이용한 항법시스템 설계)

  • Kim, Jin-Won;Jee, Gyu-In;Lee, Jang-Gyu;Lee, Young-Jae
    • Journal of Institute of Control, Robotics and Systems
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    • v.2 no.3
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    • pp.188-193
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    • 1996
  • In this paper, an integrated navigation system based on GPS(Global Positioning System) and Dead-Reckoning (DR) is designed. For the calibration of DR, a self-calibration method and a GPS-based calibration method are proposed. From the field-test results, it is shown that DR can be successfully calibrated by the two proposed calibration methods. Also, a cascaded filter approach and a mixed-measurement algorithm are employed for GPS/DR integration. By using the newly proposed mixed-measurement algorithm, it is shown in simulation that the position error becomes smaller than by using only DR even if the number of visible GPS satellites is less than 4.

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Likelihood-Based Inference on Genetic Variance Component with a Hierarchical Poisson Generalized Linear Mixed Model

  • Lee, C.
    • Asian-Australasian Journal of Animal Sciences
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    • v.13 no.8
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    • pp.1035-1039
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    • 2000
  • This study developed a Poisson generalized linear mixed model and a procedure to estimate genetic parameters for count traits. The method derived from a frequentist perspective was based on hierarchical likelihood, and the maximum adjusted profile hierarchical likelihood was employed to estimate dispersion parameters of genetic random effects. Current approach is a generalization of Henderson's method to non-normal data, and was applied to simulated data. Underestimation was observed in the genetic variance component estimates for the data simulated with large heritability by using the Poisson generalized linear mixed model and the corresponding maximum adjusted profile hierarchical likelihood. However, the current method fitted the data generated with small heritability better than those generated with large heritability.

A Neuro-Fuzzy Model Approach for the Land Cover Classification

  • Han, Jong-Gyu;Chi, Kwang-Hoon;Suh, Jae-Young
    • Proceedings of the KSRS Conference
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    • 1998.09a
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    • pp.122-127
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    • 1998
  • This paper presents the neuro-fuzzy classifier derived from the generic model of a 3-layer fuzzy perceptron and developed the classification software based on the neuro-fuzzl model. Also, a comparison of the neuro-fuzzy and maximum-likelihood classifiers is presented in this paper. The Airborne Multispectral Scanner(AMS) imagery of Tae-Duk Science Complex Town were used for this comparison. The neuro-fuzzy classifier was more considerably accurate in the mixed composition area like "bare soil" , "dried grass" and "coniferous tree", however, the "cement road" and "asphalt road" classified more correctly with the maximum-likelihood classifier than the neuro-fuzzy classifier. Thus, the neuro-fuzzy model can be used to classify the mixed composition area like the natural environment of korea peninsula. From this research we conclude that the neuro-fuzzy classifier was superior in suppression of mixed pixel classification errors, and more robust to training site heterogeneity and the use of class labels for land use that are mixtures of land cover signatures.

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Bayesian Hierarchical Mixed Effects Analysis of Time Non-Homogeneous Markov Chains (계층적 베이지안 혼합 효과 모델을 사용한 비동차 마코프 체인의 분석)

  • Sung, Minje
    • The Korean Journal of Applied Statistics
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    • v.27 no.2
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    • pp.263-275
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    • 2014
  • The present study used a hierarchical Bayesian approach was used to develop a mixed effect model to describe the transitional behavior of subjects in time nonhomogeneous Markov chains. The posterior distributions of model parameters were not in analytically tractable forms; subsequently, a Gibbs sampling method was used to draw samples from full conditional posterior distributions. The proposed model was implemented with real data.

Analysis of Stratified Lake using an Eddy Diffusion and a Mixed-layer Models

  • Kim, Kyung-sub
    • Korean Journal of Hydrosciences
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    • v.8
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    • pp.111-123
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    • 1997
  • A one-dimensional eddy diffusion model and a mixed-layer model are developed and applied to simulate the vertical temperature profiles in lakes. Also the running result of each method are compared and analyzed. In an eddy diffusion model, molecular diffusivity is neglected and eddy diffusivity which does not need lake-specific fitting parameter and constant lake's level are applied. The heat exchanges at the water surface and the bottom are formulated by the energy balance and zero energy gradient, respectively. In a mixed-layer model, two layers approach which has a constant thickness is adopted. The application of these models which use explicit finite difference and Runge-Kutta methods respectively demonstrates that the models simulate water temperatures efficiently.

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Balancing and sequencing mixed-model U-lines using evolutionary algorithm (진화알고리듬을 이용한 혼합모델 U라인의 작업할당과 투입순서 결정)

  • Kim Jae Yun;Kim Yeo Geun
    • Proceedings of the Korean Operations and Management Science Society Conference
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    • 2002.05a
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    • pp.930-935
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    • 2002
  • This paper presents a new method that can efficiently solve the integrated problem of line balancing and model sequencing in mixed-model U-lines (MMULs). Balancing and sequencing problem are important for an efficient use of MMULs and are tightly related with each other. However, in almost all the existing researches on mixed­model production lines, the two problems have been considered separately. In 1his research, an endosymbiotic evolutionary algorithm, which is a kind of evolutionary algorithm, is adopted as a methodology in order to solve the two problems simultaneously. Some evolutionary search capability, rapidity of convergence and population diversity. The proposed algorithm is compared with the existing evolutionary algorithm in terms of solution quality. The experimental results confirm the effectiveness of our approach.

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Estimating the Value of Multiple Destination Trips : A Mixed Logit Approach (혼합로짓모형을 이용한 다목적지 여행의 편익 분석)

  • Lee, Hae-Jin;Kwon, Oh-Sang
    • Environmental and Resource Economics Review
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    • v.19 no.3
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    • pp.547-569
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    • 2010
  • The purpose of this study is to estimate the benefits associated with the opportunities of multiple destination trips using a mixed logit model. The opportunities that affect the destination choice can be one of the external environments of recreational sites. The data for this study were taken from a survey conducted to the multiple destination trip participants at Seorak National Park in Korea. The results of the research show the specific values of complementary opportunities in the study area.

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Analysis of periodontal data using mixed effects models

  • Cho, Young Il;Kim, Hae-Young
    • Journal of Periodontal and Implant Science
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    • v.45 no.1
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    • pp.2-7
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    • 2015
  • A fundamental problem in analyzing complex multilevel-structured periodontal data is the violation of independency among the observations, which is an assumption in traditional statistical models (e.g., analysis of variance and ordinary least squares regression). In many cases, aggregation (i.e., mean or sum scores) has been employed to overcome this problem. However, the aggregation approach still exhibits certain limitations, such as a loss of power and detailed information, no cross-level relationship analysis, and the potential for creating an ecological fallacy. In order to handle multilevel-structured data appropriately, mixed effects models have been introduced and employed in dental research using periodontal data. The use of mixed effects models might account for the potential bias due to the violation of the independency assumption as well as provide accurate estimates.

GENIIS, a New Hybrid Algorithm for Solving the Mixed Chinese Postman Problem

  • Choi, Myeong-Gil;Thangi, Nguyen-Manh;Hwang, Won-Joo
    • The Journal of Information Systems
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    • v.17 no.3
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    • pp.39-58
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    • 2008
  • Mixed Chinese Postman Problem (MCPP) is a practical generalization of the classical Chinese Postman Problem (CPP) and it could be applied in many real world. Although MCPP is useful in terms of reality, MCPP has been proved to be a NP-complete problem. To find optimal solutions efficiently in MCPP, we can reduce searching space to be small effective searching space containing optimal solutions. We propose GENIIS methodology, which is a kind of hybrid algorithm combines the approximate algorithms and genetic algorithm. To get good solutions in the effective searching space, GENIIS uses approximate algorithm and genetic algorithm. This paper validates the usefulness of the proposed approach in a simulation. The results of our paper could be utilized to increase the efficiencies of network and transportation in business.

Sequencing Problem to Keep a Constant Rate of Part Usage In Mixed Model Assembly Lines : A Genetic Algorithm Approach (혼합모델 조립라인에서 부품사용의 일정률 유지를 위한 생산순서 결정 : 유전알고리즘 적용)

  • Hyun, Chul-Ju
    • Journal of the Korea Safety Management & Science
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    • v.9 no.4
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    • pp.129-136
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    • 2007
  • This paper considers the sequencing of products in mixed model assembly lines under Just-In-Time (JIT) systems. Under JIT systems, the most important goal for the sequencing problem is to keep a constant rate of usage every part used by the systems. The sequencing problem is solved using Genetic Algorithm Genetic Algorithm is a heuristic method which can provide a near optimal solution in real time. The performance of proposed technique is compared with existing heuristic methods in terms of solution quality. Various examples are presented and experimental results are reported to demonstrate the efficiency of the technique.