Results 31 to 40 of about 35,745,185 (300)

Towards Analysis of Multivariate Time Series Using Topological Data Analysis

Mathematics
Topological data analysis (TDA) has proven to be a potent approach for extracting intricate topological structures from complex and high-dimensional data.
Jingyi Zheng, Ziqin Feng, Arne D. Ekstrom   +2 more
doaj   +1 more source

Groundwater level forecast based on principal component analysis and multivariate time series model

Shui kexue jinzhan, 2017
Predication of groundwater level is an important basis for the management of regional water resources. Based on the high randomness and hysteresis characteristics of groundwater in time series, a groundwater level prediction model that is based on ...
ZHANG Zhanyu, LIANG Zhenhua, FENG Baoping, HUANG Jiwen, WU Dong   +4 more
doaj   +1 more source

Deep Learning for Anomaly Detection in Time-Series Data: An Analysis of Techniques, Review of Applications, and Guidelines for Future Research

IEEE Access
Industries are generating massive amounts of data due to increased automation and interconnectedness. As data from various sources becomes more available, the extraction of relevant information becomes crucial for understanding complex systems’ ...
Usman Ahmad Usmani, Izzatdin Abdul Aziz, Jafreezal Jaafar, Junzo Watada   +3 more
doaj   +1 more source

Incorporation of causality structures to complex network analysis of time-varying behaviour of multivariate time series

Scientific Reports, 2021
This paper presents a new methodology for characterising the evolving behaviour of the time-varying causality between multivariate time series, from the perspective of change in the structure of the causality pattern.
Leo Carlos-Sandberg, Christopher D. Clack   +1 more
doaj   +1 more source

Multivariate analysis in vector time series [PDF]

, 2001
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. Some of the results obtained in the time domain are reviewed.
Peña, Daniel, Galeano, Pedro
openaire   +2 more sources

Adaptive Bayesian Time–Frequency Analysis of Multivariate Time Series [PDF]

Journal of the American Statistical Association, 2018
This article introduces a nonparametric approach to multivariate time-varying power spectrum analysis. The procedure adaptively partitions a time series into an unknown number of approximately stationary segments, where some spectral components may remain unchanged across segments, allowing components to evolve differently over time.
Zeda Li, Robert T. Krafty
openaire   +2 more sources

Design and analysis strategies for robust microbiome ageing research

FEBS Letters, EarlyView.
The gut microbiome changes with age and associates with age‐related morbidity and mortality, establishing it as a potential biomarker and intervention target for ageing. Realising this potential requires methodological rigour, yet distinguishing biological signals from methodological artefacts remains challenging across cohorts. This review provides an
Mark Olenik, İsmail Güderer, Yi Wang, Tayyaba Alvi, Prasoon Pandey, Handan Melike Dönertaş   +5 more
wiley   +1 more source

Forecasting municipal waste accumulation rate and personal consumption expenditures using vector autoregressive (VAR) model

Production Engineering Archives, 2022
Accurate forecasting of municipal solid waste (MSW) generation is important for the planning, operation and optimization of municipal waste management system.
Bień Jurand
doaj   +1 more source

Developmental programmes drive cellular plasticity, disease progression and therapy resistance in lung adenocarcinoma

Molecular Oncology, EarlyView.
This study shows that lung adenocarcinomas exploit developmental branching morphogenesis to acquire a therapy resistant basal‐like tumour cell state. This process was found to be regulated by combined TP53 loss‐of‐function and type‐I interferon signalling, identifying a novel axis for biomarker and therapeutic target discovery.
Kamila J Bienkowska, Stephany Gallardo, Nur S. Zainal, Leena Arora, Matthew Ellis, Maria‐Antoinette Lopez, Judith Austine, Sai Pittla, Serena J Chee, Aiman Alzetani, Emily C Shaw, Christian H Ottensmeier, Gareth J Thomas, Christopher J Hanley   +13 more
wiley   +1 more source

Guidance for Interactive Visual Analysis in Multivariate Time Series Preprocessing

Sensors
Multivariate time series analysis presents significant challenges due to its dynamism, heterogeneity, and scalability. Given this, preprocessing is considered a crucial step to ensure analytical quality.
Flor de Luz Palomino Valdivia, Herwin Alayn Huillcen Baca   +1 more
doaj   +1 more source