Results 71 to 80 of about 223,849 (180)

Multivariate time series prediction based on AR_CLSTM

Journal of Measurement Science and Instrumentation, 2021
Time series is a kind of data widely used in various fields such as electricity forecasting, exchange rate forecasting, and solar power generation forecasting, and therefore time series prediction is of great significance.
QIAO Gangzhu, SU Rong, ZHANG Hongfei
doaj  

Forecastable Component Analysis (ForeCA) [PDF]

, 2013
I introduce Forecastable Component Analysis (ForeCA), a novel dimension reduction technique for temporally dependent signals. Based on a new forecastability measure, ForeCA finds an optimal transformation to separate a multivariate time series into a ...
Goerg, Georg M.
core  

Sparse Identification and Estimation of Large-Scale Vector AutoRegressive Moving Averages

, 2019
The Vector AutoRegressive Moving Average (VARMA) model is fundamental to the theory of multivariate time series; however, in practice, identifiability issues have led many authors to abandon VARMA modeling in favor of the simpler Vector AutoRegressive ...
Basu, Sumanta, Bien, Jacob, Matteson, David S., Wilms, Ines   +3 more
core   +1 more source

Retail Demand Forecasting: A Comparative Analysis of Deep Neural Networks and the Proposal of LSTMixer, a Linear Model Extension

Information
Accurate retail demand forecasting is integral to the operational efficiency of any retail business. As demand is described over time, the prediction of demand is a time-series forecasting problem which may be addressed in a univariate manner, via ...
Georgios Theodoridis, Athanasios Tsadiras   +1 more
doaj   +1 more source

An End-to-End Adaptive Input Selection With Dynamic Weights for Forecasting Multivariate Time Series

IEEE Access, 2019
A multivariate time series forecasting is critical in many applications, such as signal processing, finance, air quality forecasting, and pattern recognition.
Lkhagvadorj Munkhdalai, Tsendsuren Munkhdalai, Kwang Ho Park, Tsatsral Amarbayasgalan, Erdenebileg Erdenebaatar, Hyun Woo Park, Keun Ho Ryu   +6 more
doaj   +1 more source

Forecasting euro area inflation: Does aggregating forecasts by HICP component improve forecast accuracy? [PDF]

Monitoring and forecasting price developments in the euro area is essential in the light of the second pillar of the ECB's monetary policy strategy. This study analyses whether the forecasting accuracy of forecasting aggregate euro area inflation can be ...
Hubrich, Kirstin
core  

Estimating, Filtering and Forecasting Realized Betas [PDF]

A strategy for estimating, ?filtering and forecasting time-varying factor betas is proposed. The approach is based on the multivariate realized regression principle, an omnibus noise ?filter and an adaptive long memory forecasting model.
Claudio Morana
core  

Enhanced Forecasting of Groundwater Level Incorporating an Exogenous Variable: Evaluating Conventional Multivariate Time Series and Artificial Neural Network Models

Geographies
Continuous and uncontrolled extraction of groundwater often creates tremendous pressure on groundwater levels (GWLs). As a part of sustainable planning and effective management of water resources, it is crucial to assess the existing and forecasted GWL ...
Md Abrarul Hoque, Asib Ahmmed Apon, Md Arafat Hassan, Sajal Kumar Adhikary, Md Ariful Islam   +4 more
doaj   +1 more source

Granular Weighted Fuzzy Approach Applied to Short-Term Load Demand Forecasting

Technologies
The development of accurate models to forecast load demand across different time horizons is challenging due to demand patterns and endogenous variables that affect short-term and long-term demand. This paper presents two contributions.
Cesar Vinicius Züge, Leandro dos Santos Coelho   +1 more
doaj   +1 more source

Comparing Short-Term Univariate and Multivariate Time-Series Forecasting Models in Infectious Disease Outbreak. [PDF]

Bull Math Biol, 2022
Assad DBN, Cara J, Ortega-Mier M.
europepmc   +1 more source