Results 211 to 220 of about 50,820 (258)

FORECASTING TIME SERIES USING WAVELETS

International Journal of Wavelets, Multiresolution and Information Processing, 2007
This paper deals with wavelets in time series, focusing on statistical forecasting purposes. Recent approaches involve wavelet decompositions in order to handle non-stationary time series in such context. A method, proposed by Renaud et al.,11 estimates directly the prediction equation by direct regression of the process on the Haar non-decimated ...
Mina Aminghafari, Jean-Michel Poggi
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Relational time series forecasting

The Knowledge Engineering Review, 2018
Abstract Networks encode dependencies between entities (people, computers, proteins) and allow us to study phenomena across social, technological, and biological domains. These networks naturally evolve over time by the addition, deletion, and changing of links, nodes, and attributes.
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Forecasting With time Series Models

2002
Having selected a model and fitted its parameters to a given times series, the model can then be used to estimate new data of the time series. If such data are estimated for a time period following the final data value X T of the given time series, we speak of a prediction or forecast.
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Ensemble Time Series Forecasting with XCSF

2016 IEEE 10th International Conference on Self-Adaptive and Self-Organizing Systems (SASO), 2016
Time series forecasting constitutes an important aspect of any technical system, since the underlying data generating processes vary over time. In order to take system designers out of the loop, efforts for designing self-adaptive, learning systems have extensively been made. By means of forecasting the succeeding system state, the system is enabled to
Matthias Sommer, Anthony Stein, Jörg Hähner   +2 more
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Time Series Forecasting

2012
Nowcasting global solar irradiance on very short time horizons is the principal topic discussed in this chapter. Various ARIMA models for nowcasting clearness index are inferred and assessed. Radiometric data measured at 15 s lag during June 2010 in Timisoara (Romania) are used for setting up and testing the models.
Marius Paulescu, Eugenia Paulescu, Paul Gravila, Viorel Badescu   +3 more
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Forecasting Time Series

2011
This chapter includes two problems for forecasting of a time series using past data points. It is argued that the past data points used for forecasting of the future data points should be strongly correlated with each other. It is illustrated that the strongly correlated past data points can be identified from the autocorrelation function of the time ...
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Time-Series Forecasting

Technometrics, 2002
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Time Series Forecasting

2008
La previsione della domanda commerciale viene generata mediante l’impiego di modelli matematici di Sales Forecasting, i quali analizzano i valori disponibili delle vendite realizzate nel passato, interpretano i fenomeni di regolarita nella domanda e proiettano le componenti delle serie storiche nel futuro, dando luogo al piano previsionale di domanda ...
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Time Series Forecasting

2019
Forecasting is important in economics, commerce and various disciplines of social science and pure science. Forecasting is a method for computing future values by analysing the behaviour of present and past values of a time series. Forecasting model may be univariate or multivariate.
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An Experimental Review on Deep Learning Architectures for Time Series Forecasting

International Journal of Neural Systems, 2021
Manuel Carranza-García, JOSÉ C Riquelme, Pedro Lara-Benítez   +2 more
exaly