Results 21 to 30 of about 517,907 (286)
, 2015 In this chapter four combinations of input features and the feedforward, cascade forward and recurrent architectures are compared for the task of forecast tourism time series. The input features of the ANNs consist in the combination of the previous 12 months, the index time modeled by two nodes used to the year and month and one input with the daily ...
Teixeira, João Paulo +1 more
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Forecasting Economic Time Series
, 1998 This book provides a formal analysis of the models, procedures, and measures of economic forecasting with a view to improving forecasting practice. David Hendry and Michael Clements base the analyses on assumptions pertinent to the economies to be forecast, viz.
Clements, M, Hendry, D
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TIME SERIES FORECASTING USING NEURAL NETWORKS [PDF]
Challenges of the Knowledge Society, 2013 Recent studies have shown the classification and prediction power of the Neural Networks. It has been demonstrated that a NN can approximate any continuous function.
BOGDAN OANCEA, ŞTEFAN CRISTIAN CIUCU
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Probabilistic-Based Forecasting Method For Time Series Datasets
Düzce Üniversitesi Bilim ve Teknoloji Dergisi, 2023 In this paper, a new probabilistic technique (a variant of Multiple Model Particle Filter-MMPF) will be used to predict time-series datasets. At first, the reliable performance of our method is proved using a virtual random scenario containing sixty ...
Abdullatif Baba
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Robust Multi-Dimensional Time Series Forecasting
EntropyLarge-scale and high-dimensional time series data are widely generated in modern applications such as intelligent transportation and environmental monitoring. However, such data contains much noise, outliers, and missing values due to interference during
Chen Shen, Yong He, Jin Qin
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Forecasting Hierarchical Time Series in Power Generation
Energies, 2020 Academic attention is being paid to the study of hierarchical time series. Especially in the electrical sector, there are several applications in which information can be organized into a hierarchical structure.
Tiago Silveira Gontijo +1 more
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Forecasting With Nonlinear Time Series Models [PDF]
SSRN Electronic Journal, 2010 AbstractThis article considers nonlinear forecasting models, such as switching-regime models. These models are typically “small” compared to vector autoregressive and factor models, being either univariate or single-equation models, but tend to nest a linear relationship and so invite an assessment of whether allowing for nonlinearity improves forecast
Kock, Anders Bredahl, Teräsvirta, Timo
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With string model to time series forecasting
, 2015 Overwhelming majority of econometric models applied on a long term basis in the financial forex market do not work sufficiently well. The reason is that transaction costs and arbitrage opportunity are not included, as this does not simulate the real ...
Bartoš, Erik, Pinčák, Richard
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Economic forecasting in a changing world [PDF]
, 2008 This article explains the basis for a theory of economic forecasting developed over the past decade by the authors. The research has resulted in numerous articles in academic journals, two monographs, Forecasting Economic Time Series, 1998, Cambridge ...
Clements, Michael P., Hendry, David F.
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HUTFormer: Hierarchical U-Net transformer for long-term traffic forecasting
Communications in Transportation ResearchTraffic forecasting, which aims to predict traffic conditions based on historical observations, has been an enduring research topic and is widely recognized as an essential component of intelligent transportation.
Zezhi Shao +9 more
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