Detecting structural breaks in time series via genetic algorithms
作者: Benjamin DoerrPaul FischerAstrid HilbertCarsten Witt
作者单位: 1École Polytechnique
2DTU Compute Technical University of Denmark
3Mathematics Linnaeus University
刊名: Soft Computing, 2017, Vol.21 (16), pp.4707-4720
来源数据库: Springer Nature Journal
DOI: 10.1007/s00500-016-2079-0
关键词: Genetic AlgorithmsStatisticsBreak pointsExperimentationTime seriesRange trees
英文摘要: Detecting structural breaks is an essential task for the statistical analysis of time series, for example, for fitting parametric models to it. In short, structural breaks are points in time at which the behaviour of the time series substantially changes. Typically, no solid background knowledge of the time series under consideration is available. Therefore, a black-box optimization approach is our method of choice for detecting structural breaks. We describe a genetic algorithm framework which easily adapts to a large number of statistical settings. To evaluate the usefulness of different crossover and mutation operations for this problem, we conduct extensive experiments to determine good choices for the parameters and operators of the genetic algorithm. One surprising observation is...
原始语种摘要: Detecting structural breaks is an essential task for the statistical analysis of time series, for example, for fitting parametric models to it. In short, structural breaks are points in time at which the behaviour of the time series substantially changes. Typically, no solid background knowledge of the time series under consideration is available. Therefore, a black-box optimization approach is our method of choice for detecting structural breaks. We describe a genetic algorithm framework which easily adapts to a large number of statistical settings. To evaluate the usefulness of different crossover and mutation operations for this problem, we conduct extensive experiments to determine good choices for the parameters and operators of the genetic algorithm. One surprising observation is...
全文获取路径: Springer Nature  (合作)
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影响因子:1.124 (2012)

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关键词翻译
关键词翻译
  • genetic 遗传的
  • breaks 劣地形
  • structural 构造
  • available 可供应的
  • evaluate 求...的值
  • series 
  • crossover 交叉
  • together 共同
  • extensive 广泛的
  • operator 话务员