Results 41 to 50 of about 13,606,645 (327)
Visibility Graph Based Time Series Analysis. [PDF]
PLoS ONE, 2015 Network based time series analysis has made considerable achievements in the recent years. By mapping mono/multivariate time series into networks, one can investigate both it's microscopic and macroscopic behaviors. However, most proposed approaches lead
Mutua Stephen, Changgui Gu, Huijie Yang
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Eddies: Fluid Dynamical Niches or Transporters?–A Case Study in the Western Baltic Sea
Frontiers in Marine Science, 2019 Fluid flows in the ocean have a strong impact on the growth and distribution of planktonic communities. In this case study, we applied a Lagrangian eddy detection and tracking tool and a transfer operator approach to data from a coupled hydrodynamical ...
Rahel Vortmeyer-Kley +5 more
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On predicting climate under climate change
Environmental Research Letters, 2013 Can today’s global climate model ensembles characterize the 21st century climate in their own ‘model-worlds’? This question is at the heart of how we design and interpret climate model experiments for both science and policy support.
Joseph D Daron, David A Stainforth
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Time Series Segmentation Based on Stationarity Analysis to Improve New Samples Prediction
Sensors, 2021 A wide range of applications based on sequential data, named time series, have become increasingly popular in recent years, mainly those based on the Internet of Things (IoT).
Ricardo Petri Silva +3 more
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Time series data analysis under indeterminacy
Journal of Big Data, 2023 The existing semi-average method under classical statistics is applied to measure the trend in the time series data. The existing semi-average method cannot be applied when the time series data is in intervals or imprecise.
Muhammad Aslam
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Multivariate analysis in vector time series [PDF]
This paper reviews the applications of classical multivariate techniques for discrimination, clustering and dimension reduction for time series data. It is shown that the discrimination problem can be seen as a model selection problem.
Galeano, Pedro, Peña, Daniel
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EntropyHub: An open-source toolkit for entropic time series analysis
PLoS ONE, 2021 An increasing number of studies across many research fields from biomedical engineering to finance are employing measures of entropy to quantify the regularity, variability or randomness of time series and image data.
M. Flood, Bernd Grimm
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Statistical analysis of medical time series
Journal of V. N. Karazin Kharkiv National University: Series Medicine, 2020 Statistical analysis of data sets is a necessary component of any medical research. Modern methods of mathematical statistics and statistical application suites provide extensive capabilities for analysis of random values.
Alexander Martynenko +3 more
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A Machine-Learning Framework for Modeling and Predicting Monthly Streamflow Time Series
Hydrology, 2023 Having a complete hydrological time series is crucial for water-resources management and modeling. However, this can pose a challenge in data-scarce environments where data gaps are widespread.
Hatef Dastour, Quazi K. Hassan
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A Novel Method for IPTV Customer Behavior Analysis Using Time Series
IEEE Access, 2022 Internet Protocol Television (IPTV) has had a significant impact on live TV content consumption in the past decade, as improvements in the broadband speed have allowed more data volume to be delivered.
Tomislav Hlupic +2 more
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