.png){kind=icon}
返回
Memetic algorithm for multivariate time-series segmentation
.png){kind=icon}
PRE
AI
DOI：10.1016/j.patrec.2020.06.022.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
In recent years, analyzing time-series data has become an ever important research topic due to an increased number of temporal datasets in science and engineering. Segmentation is widely used in time-series data analysis because it provides a more compact representation by dividing the series into segments. Segmentation approaches based on genetic algorithms have been proposed to extract segments and patterns with a given objective, such as a low rate of change or periodicity from time-series data. However, they may not be effective in obtaining the precise solution because they perform global search. In this study, we propose a memetic algorithm for multivariate time-series segmentation. For efficient local refinement, we calculate a likelihood-based score for all time points and use it in the evolutionary process. Experiments demonstrate that the proposed method is superior to conventional segmentation methods. The source code of the proposed method can be downloaded from https://github.com/hlim-kist/ma_mts (C) 2020 Elsevier B.V. All rights reserved.
Keyword:
Time series segmentation
Multivariate data
Memetic algorithm
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
3.3
论文数:
7.9K
被引数:
1.6W
机构
引用论文
Accurate occupancy detection of an office room from light, temperature, humidity and CO2 measurements using statistical learning models.png)
ENERGY AND BUILDINGS
ENERGY AND BUILDINGSIF7.1
PREAI
分享收藏A hybrid dynamic exploitation barebones particle swarm optimisation algorithm for time series segmentationNEUROCOMPUTING
OAAI
NEUROCOMPUTINGIF6.5
OAAI分享收藏分享收藏分享收藏The influence of comorbidities on mortality in bronchiectasis: A prospective, observational study
OAAI
OAAI分享收藏DSTP-RNN: A dual-stage two-phase attention-based recurrent neural network for long-term and multivariate time series predictionDstp-rnn: 用于长期和多变量时间序列预测的基于双阶段两阶段注意力的递归神经网络
PREAI
分享收藏
查看更多内容