Results 91 to 100 of about 35,745,185 (300)
A Review of Explainable Semi–Supervised Methods in Multivariate Time Series Analysis
International Journal of Applied Mathematics and Computer ScienceRecent advances in information and communication technologies have led to the widespread use of smart meters, wearable sensors, and related devices in healthcare, industrial monitoring (e.g., manufacturing and energy systems), and transportation.
Wichrowski Filip +3 more
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IEEE Access, 2019 The high dimension of multivariate time series (MTS) is one of the major factors that impact on the efficiency and effectiveness of data mining. It has two kinds of dimensions, time-based dimensionality, and variable-based dimensionality.
Hailin Li +3 more
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, 1973 The first issue of the Journal of Multivariate Experimental Personality and Clinical Psychology edited by G.R. Pierson. Editorial policy board: Raymond B. Cattell, Hans J. Eysenck, Joy P. Guilford and Paul E. Meehl.Digitized and published in SOAR:Shocker
Western Institute of Multivariate Experimental Psychology
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Rainfall Shapes the Diversity of Soil Nitrogen‐Fixing Microorganisms Worldwide
Advanced Science, EarlyView.This study reveals the distinctive pattern and mechanism of rainfall driving the global biodiversity and biogeography of soil potential N‐fixing microorganisms, and constructs the theoretical framework. The results guide us on how to maintain ecosystem productivity under future climate changes (e.g., whether a specific region needs more N fertilizers ...
Bin Hua +18 more
wiley +1 more source
A time–frequency contrastive learning model for anomaly detection in multivariate time series
Complex & Intelligent SystemsAnomaly detection in multivariate time series is critical for applications such as industrial maintenance, early warning systems, and environmental monitoring. However, existing reconstruction-based models often exhibit poor generalization and high false-
Wei Zhang +6 more
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New multivariate time-series estimators in Stata [PDF]
Stata 11 has new commands sspace and dvech for estimating the parameters of space-space models and diagonal-vech multivariate GARCH models, respectively.
David M. Drukker
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Advanced Science, EarlyView.We report the rational design of artificial photocatalysts with asymmetrically coordinated dual‐metal centers and a tailored microenvironment, broadly applicable strategy is established for the synthesis of multivariate zirconium‐based metal–organic frameworks, offering a platform for precisely tuning active‐site configurations to optimize ...
Yuxin Lu +11 more
wiley +1 more source
IEEE Journal of Selected Topics in Applied Earth Observations and Remote SensingThis article explores the use of Fisher discriminant analysis (FDA) as a method for extracting time-resolved information from multivariate environmental time series data.
Conor T. Doherty, Meagan S. Mauter
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Advanced Science, EarlyView.A unified time‐series forecasting framework learns transferable battery capacity‐degradation patterns from 20 heterogeneous datasets spanning chemistries, formats, temperatures, and cycling conditions. A single model delivers competitive predictions on both known and previously unseen datasets, while physics‐guided representation learning improves ...
Joey Chan +8 more
wiley +1 more source
Fractional integration and cointegration in US financial time series data [PDF]
, 2011 This paper examines several US monthly financial time series data using fractional integration and cointegration techniques. The univariate analysis based on fractional integration aims to determine whether the series are I(1) (in which case markets ...
Gil-Alana, Luis A. +5 more
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