Results 11 to 20 of about 1,758,719 (322)
On the Prediction of Stationary Functional Time Series [PDF]
Journal of the American Statistical Association, 2015 This paper addresses the prediction of stationary functional time series. Existing contributions to this problem have largely focused on the special case of first-order functional autoregressive processes because of their technical tractability and the current lack of advanced functional time series methodology.
Aue, Alexander +2 more
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Grammar-Mediated Time-Series Prediction
Journal of Intelligent Systems, 2005 Brabazon, A. +4 more
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Review of Deep Learning Applied to Time Series Prediction [PDF]
Jisuanji kexue yu tansuo, 2023 The time series is generally a set of random variables that are observed and collected at a certain frequency in the course of something??s development.
LIANG Hongtao, LIU Shuo, DU Junwei, HU Qiang, YU Xu
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On predictability of time series [PDF]
Physica A: Statistical Mechanics and its Applications, 2019 The method to estimate the predictability of human mobility was proposed in [C. Song \emph{et al.}, Science {\bf 327}, 1018 (2010)], which is extensively followed in exploring the predictability of disparate time series. However, the ambiguous description in the original paper leads to some misunderstandings, including the inconsistent logarithm bases ...
Paiheng Xu +5 more
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Prediction in Locally Stationary Time Series [PDF]
Journal of Business & Economic Statistics, 2020 We develop an estimator for the high-dimensional covariance matrix of a locally stationary process with a smoothly varying trend and use this statistic to derive consistent predictors in nonstationary time series. In contrast to the currently available methods for this problem the predictor developed here does not rely on fitting an autoregressive ...
Holger Dette, Weichi Wu
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Robust Interval Prediction of Intermittent Demand for Spare Parts Based on Tensor Optimization
Sensors, 2023 Demand for spare parts, which is triggered by element failure, project schedule and reliability demand, etc., is a kind of sensing data to the aftermarket service of large manufacturing enterprises.
Kairong Hong +4 more
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Predicting chaotic time series [PDF]
Physical Review Letters, 1987 We present a forecasting technique for chaotic data. After embedding a time series in a state space using delay coordinates, we ``learn'' the induced nonlinear mapping using local approximation. This allows us to make short-term predictions of the future behavior of a time series, using information based only on past values.
Farmer, J. Doyne, Sidorowich, John J.
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Temperature Time Series Prediction Model Based on Time Series Decomposition and Bi-LSTM Network
Mathematics, 2023 Utilizing a temperature time-series prediction model to achieve good results can help us to accurately sense the changes occurring in temperature levels in advance, which is important for human life.
Kun Zhang, Xing Huo, Kun Shao
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Time Series Prediction Based on LSTM-Attention-LSTM Model
IEEE Access, 2023 Time series forecasting uses data from the past periods of time to predict future information, which is of great significance in many applications. Existing time series forecasting methods still have problems such as low accuracy when dealing with some ...
Xianyun Wen, Weibang Li
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Self-Attentive Moving Average for Time Series Prediction
Applied Sciences, 2022 Time series prediction has been studied for decades due to its potential in a wide range of applications. As one of the most popular technical indicators, moving average summarizes the overall changing patterns over a past period and is frequently used ...
Yaxi Su, Chaoran Cui, Hao Qu
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