论文标题

具有贝叶斯方法的遗传算法,用于检测特定阈值的计数超过计数时间序列的多个点

Genetic algorithm with a Bayesian approach for the detection of multiple points of change of time series of counting exceedances of specific thresholds

论文作者

Suárez-Sierra, Biviana Marcela, Coen, Arrigo, Taimal, Carlos Alberto

论文摘要

尽管事实证明,非均匀泊松过程的应用在不同时间序列中建模和研究的阈值超出感感兴趣的阈值超出了良好的结果可以提供良好的效果,但它们需要采用有效且自动的诊断技术来补充,以建立变更点的位置,并在考虑到估计模型的情况下,这些变化点拟合了众多的信息,这些模型符合这些信息的信息,这些模型包含了实际的模型。因此,我们提出了一种解决时间序列的分割不确定性的新方法,其中特定阈值超出超出的排放分布是研究的重点。当前算法的巨大贡献之一是,溢出的所有日子都是候选者成为变更点的,因此溢出天的所有可能配置都是可能的染色体,这将统一具有后代。在遗传算法的启发式下,解决此类变化点的问题的解决方案将被保证是非本地的,并且可能是最好的,从而减少了浪费的机器时间,评估最小可能的染色体可以解决该问题。分析评估技术将通过最小描述长度(\ textit {mdl})作为目标函数,这是每个制度参数的联合后验分布函数,以及确定它们的变化点以及确定它们的变化点的影响。

Although the applications of Non-Homogeneous Poisson Processes to model and study the threshold overshoots of interest in different time series of measurements have proven to provide good results, they needed to be complemented with an efficient and automatic diagnostic technique to establish the location of the change-points, which, when taken into account, make the estimated model fit poorly in regards of the information contained in the real model. For this reason, we propose a new method to solve the segmentation uncertainty of the time series of measurements, where the emission distribution of exceedances of a specific threshold is the focus of investigation. One of the great contributions of the present algorithm is that all the days that overflowed are candidates to be a change-point, so all the possible configurations of overflow days are the possible chromosomes, which will unite to have offspring. Under the heuristics of a genetic algorithm, the solution to the problem of finding such change points will be guaranteed to be non-local and the best possible one, reducing wasted machine time evaluating the least likely chromosomes to be a solution to the problem. The analytical evaluation technique will be by means of the Minimum Description Length (\textit{MDL}) as the objective function, which is the joint posterior distribution function of the parameters of each regime and the change points that determines them and which account as well for the influence of the presence of said times.

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