Results 21 to 30 of about 10,612,437 (315)
Multivariate dynamic kernels for financial time series forecasting [PDF]
, 2016 The final publication is available at http://link.springer.com/chapter/10.1007/978-3-319-44781-0_40We propose a forecasting procedure based on multivariate dynamic kernels, with the capability of integrating information measured at different frequencies ...
AJ Smola +6 more
core +1 more source
A Novel Time-Sensitive Composite Similarity Model for Multivariate Time-Series Correlation Analysis
Entropy, 2021 Finding the correlation between stocks is an effective method for screening and adjusting investment portfolios for investors. One single temporal feature or static nontemporal features are generally used in most studies to measure the similarity between
Mengxia Liang +2 more
doaj +1 more source
GNSSseg, a Statistical Method for the Segmentation of Daily GNSS IWV Time Series
Remote Sensing, 2022 Homogenization is an important and crucial step to improve the usage of observational data for climate analysis. This work is motivated by the analysis of long series of GNSS Integrated Water Vapour (IWV) data, which have not yet been used in this ...
Annarosa Quarello +2 more
doaj +1 more source
Learning Manifolds from Dynamic Process Data
Algorithms, 2020 Scientific data, generated by computational models or from experiments, are typically results of nonlinear interactions among several latent processes. Such datasets are typically high-dimensional and exhibit strong temporal correlations.
Frank Schoeneman +4 more
doaj +1 more source
Dynamic clustering of time series with Echo State Networks [PDF]
, 2019 In this paper we introduce a novel methodology for unsupervised analysis of time series, based upon the iterative implementation of a clustering algorithm embedded into the evolution of a recurrent Echo State Network.
A Saxena +10 more
core +1 more source
Dynamic Similar Sub-Series Selection Method for Time Series Forecasting
IEEE Access, 2018 Accumulation of influencing factors during several consecutive time periods makes the variation of target parameters lag behind the variation of their influencing factors.
Peiqiang Li +6 more
doaj +1 more source
Reconstruction of Satellite Time Series With a Dynamic Smoother
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2022 Time series reconstruction methods are widely used to generate smooth and gap-free time series using imagery acquired at coarse spatial resolution and high frequency return intervals. However, as interest has grown in leveraging the nearly 40-a record of
Jordan Graesser +2 more
doaj +1 more source
Dynamic memristor-based reservoir computing for high-efficiency temporal signal processing
Nature Communications, 2021 Reservoir computing is a highly efficient network for processing temporal signals due to its low training cost compared to standard recurrent neural networks, and generating rich reservoir states is critical in the hardware implementation.
Yanan Zhong +5 more
semanticscholar +1 more source
Dynamic Multiscale Information Spillover among Crude Oil Time Series
Entropy, 2022 This study investigated information spillovers across crude oil time series at different time scales, using a network combined with a wavelet transform. It can detect the oil price, which plays an important role in the dynamic process of spillovers, and ...
Sufang An
doaj +1 more source
Time2Graph: Revisiting Time Series Modeling with Dynamic Shapelets [PDF]
AAAI Conference on Artificial Intelligence, 2019 Time series modeling has attracted extensive research efforts; however, achieving both reliable efficiency and interpretability from a unified model still remains a challenging problem.
Ziqiang Cheng +5 more
semanticscholar +1 more source