Results 61 to 70 of about 223,849 (180)

An Efficient Solution for Multivariate Time Series Forecasting Based on a Stacked Complex Fuzzy Gated Recurrent Neural Network

IEEE Access
Multivariate Time series forecasting finds numerous applications across various fields, including society, industry, market, etc. Recently, gated recurrent unit neural networks (GRU) have shown high efficiency in processing sequential time series data in
Nguyen van Quyet, Nguyen Tho Thong, Nguyen Long Giang, Luong Thi Hong Lan   +3 more
doaj   +1 more source

MCformer: Multivariate Time Series Forecasting With Mixed-Channels Transformer [PDF]

IEEE Internet of Things Journal
The massive generation of time-series data by large-scale Internet of Things (IoT) devices necessitates the exploration of more effective models for multivariate time-series forecasting.
Wenyong Han, Tao Zhu, L. Chen, Huansheng Ning, Yang Luo, Yaping Wan   +5 more
semanticscholar   +1 more source

Forecasting GNP using monthly M1 [PDF]

A presentation of multivariate time series forecasting in which the data consist of a mixture of quarterly and monthly series. In particular, a monthly series of M1 is used to forecast quarterly GNP.Time-series analysis ; Forecasting ; Gross national ...
Michael L. Bagshaw
core  

TFEformer: Temporal Feature Enhanced Transformer for Multivariate Time Series Forecasting

IEEE Access
Transformer-based models have traditionally been the primary focus of research for addressing time series forecasting challenges. However, the emergence of recently introduced high-performance linear models has cast doubt upon the effectiveness of ...
Chenhao Ying, Jiangang Lu
doaj   +1 more source

Forecasting Australian Macroeconomic variables, evaluating innovations state space approaches [PDF]

Innovations state space time series models that encapsulate the exponential smoothing methodology have been shown to be an accurate forecasting tool. These models for the first time are applied to Australian macroeconomic data.
de Silva, Ashton J
core   +1 more source

Robust exponential smoothing of multivariate time series. [PDF]

Multivariate time series may contain outliers of different types. In presence of such outliers, applying standard multivariate time series techniques becomes unreliable. A robust version of multivariate exponential smoothing is proposed.
Croux, Christophe, Gelper, Sarah, Mahieu, Koen   +2 more
core  

Multivariate time series energy forecasting using a hybrid neural-SVM ensemble model: A data-driven approach for energy management in Bangladesh

Energy Nexus
Energy forecasting of generation, demand, sources, and prices over short-time horizons is necessary for optimization of energy management. Given the increased use of developing technologies and reliance on renewable energy sources, strategic planning ...
Mohammad Mynul Islam Mahin, Md Jawad Bin Rouf, Shah Murtoza Morshed, Sheak Salman, Md Shihab Shakur, Mohammad Morshed, Md. Parvez   +6 more
doaj   +1 more source

Nonparametric modeling and forecasting electricity demand: an empirical study [PDF]

This paper uses half-hourly electricity demand data in South Australia as an empirical study of nonparametric modeling and forecasting methods for prediction from half-hour ahead to one year ahead.
Han Lin Shang
core  

Forecasting Time Series with VARMA Recursions on Graphs

, 2019
Graph-based techniques emerged as a choice to deal with the dimensionality issues in modeling multivariate time series. However, there is yet no complete understanding of how the underlying structure could be exploited to ease this task.
Isufi, Elvin, Leus, Geert, Loukas, Andreas, Perraudin, Nathanael   +3 more
core   +1 more source

Trend-Error Decomposition for Self-Supervised Time Series Learning in Multivariate Forecasting Task

IEEE Access
Self-Supervised Learning (SSL) has become a powerful paradigm in Artificial Intelligence, enabling the training of machine learning models using unlabeled data.
Sara Pederzoli, Francesco del Buono, Maurizio Vincini, Francesco Guerra   +3 more
doaj   +1 more source