A Bayesian approach for parameter estimation in railway systems

机译：铁路系统参数估计的贝叶斯方法

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摘要

In this paper, we address the problem of parameter estimation in railway systems. For this purpose, a physical model of the train based on the fundamental principle of dynamics is proposed. Then, the parameter estimation is handled via an approach using a combination of Expectation-Maximization algorithm and Sequential Monte Carlo methods. The experiments performed both on synthetic and real data show the efficiency of the considered method.

机译：在本文中，我们解决了铁路系统中参数估计的问题。为此，提出了基于动力学基本原理的列车物理模型。然后，通过使用期望最大化算法和顺序蒙特卡洛方法的组合的方法来处理参数估计。在合成和真实数据上进行的实验表明了所考虑方法的有效性。

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《International Conference on Advanced Technologies for Signal and Image Processing》|2018年|1-6|共6页
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Nouha Jaoua; Philippe Vanheeghe; Nicolas Navarro; Olivier Langlois; Marius Iordache;
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关键词
Rail transportation; Resistance; Energy consumption; Maximum likelihood estimation; Parameter estimation; Computational modeling; Acceleration;

机译：铁路运输;阻力;能耗;最大似然估计;参数估计;计算建模;加速度;

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4. A Bayesian approach for parameter estimation in railway systems [C] . Nouha Jaoua, Philippe Vanheeghe, Nicolas Navarro, International Conference on Advanced Technologies for Signal and Image Processing . 2018

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5. Approximate Bayesian Computation for Parameter Estimation in Complex Thermal-fluid Systems [D] . Christopher, Jason D. 2018

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机译：一种不确定性参数估计的贝叶斯方法动力系统

A Bayesian approach for parameter estimation in railway systems

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