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Large Multivariate Time Series Forecasting

2019
Research on the analysis of time series has gained momentum in recent years, as knowledge derived from time series analysis can improve the decision-making process for industrial and scientific fields. Furthermore, time series analysis is often an essential part of business intelligence systems.
Hmamouche, Youssef   +4 more
openaire   +2 more sources

Multivariate Time Series Analysis and Forecast

1982
It is well known that the multivariate computer-oriented methods of mathematical statistics are based on independent vector variables essentially. This is why the authors have been concerned, for a decade already, in the elaboration of procedures which could be considered as ”dynamized” variants of the principal component analysis or, in general, the ...
György Bánkövi   +2 more
openaire   +1 more source

Experimental Study of Multivariate Time Series Forecasting Models

Proceedings of the 28th ACM International Conference on Information and Knowledge Management, 2019
Multivariate time series forecasting has wide applications such as traffic flow prediction, supermarket commodity demand forecasting and etc. In literature, Due to the complex temporal patterns and inter-dependencies among multivariate time series, a large number of forecasting models have been developed.
Jiaming Yin   +7 more
openaire   +2 more sources

Forecasting traffic time series with multivariate predicting method

Applied Mathematics and Computation, 2016
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Yi Yin, Pengjian Shang
openaire   +2 more sources

Forecasting financial multivariate time series with neural networks

1st International Symposium on Neuro-Fuzzy Systems, AT '96. Conference Report, 2002
An integrated approach for modelling the behaviour of financial markets with artificial neural networks (ANNs) is presented. The method allows to forecast financial time series. Its originality lies in the fact that it is based on statistics and macroeconomics principles and it integrates fundamental economic knowledge in a multivariate nonlinear time ...
Ankenbrand, T., Tomassini, M.
openaire   +1 more source

Sequence Attention for Multivariate Time Series Forecasting

2021 IEEE Sixth International Conference on Data Science in Cyberspace (DSC), 2021
Wenrui Wu   +5 more
openaire   +2 more sources

Forecasting multivariate time series

International Journal of Forecasting, 2015
George Athanasopoulos, Farshid Vahid
openaire   +1 more source

Online Adaptive Multivariate Time Series Forecasting

2023
Amal Saadallah   +2 more
openaire   +1 more source

Deep Learning for Time Series Forecasting: Tutorial and Literature Survey

ACM Computing Surveys, 2023
Konstantinos Benidis   +2 more
exaly  

An Experimental Review on Deep Learning Architectures for Time Series Forecasting

International Journal of Neural Systems, 2021
Manuel Carranza-García   +2 more
exaly  

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