Results 21 to 30 of about 19,841,559 (252)
pohl-michel/Time-series-prediction-using-a-RNN-trained-with-RTRL: First release
, 2020 <p>Prediction of multidimensional time-series data using a recurrent neural network (RNN) trained by real-time recurrent learning (RTRL) with gradient clipping.</p ...
Pohl Michel
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Gender Prediction by Gait Analysis Based on Time Series Variation of Joint Positions [PDF]
Journal of Systemics, Cybernetics and Informatics, 2015 In this paper, a novel gender prediction scheme based on a gait analysis is proposed. For the gait analysis, we propose a novel feature extraction scheme that uses the time series vari- ation in the joint positions directly. Here, normalization by linear
Ryusuke Miyamoto, Risako Aoki
doaj
Time series prediction using artificial neural networks
Ciencias Marinas, 2002 In this work, artificial neural network (ANN) algorithms were used to predict time series of the oceanographic variables Southern Oscilation Index (SOI) and sea surface temperature anomaly (SSTA).
MA Pérez-Chavarría +2 more
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Gaussian Process priors with uncertain inputs? Application to multiple-step ahead time series forecasting [PDF]
, 2003 We consider the problem of multi-step ahead prediction in time series analysis using the non-parametric Gaussian process model. k-step ahead forecasting of a discrete-time non-linear dynamic system can be performed by doing repeated one-step ahead ...
Rasmussen, C.E. +3 more
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Multi-step learning rule for recurrent neural models: an application to time series forecasting [PDF]
, 2001 Multi-step prediction is a difficult task that has attracted increasing interest in recent years. It tries to achieve predictions several steps ahead into the future starting from current information.
Galván, Inés M. +3 more
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SoftwareXMissing data significantly hampers the analysis of time series in operational monitoring, environmental sensing, and many other domains. We present uniTS-MissRecoPred, an open-source Python library that standardizes reconstruction (imputation of missing ...
Dariusz Kobiela +3 more
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Chaotic Time-Series Prediction using Intelligent Methods [PDF]
Iranian Journal of Electrical and Electronic Engineering, 2023 Today, it can be said that in every field in which timely information is needed, we can use the applications of time-series prediction. In this paper, among so many chaotic systems, the Mackey-Glass and Loranz are chosen.
M. Nezhadshahbodaghi +3 more
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A note on prediction and interpolation errors in time series [PDF]
, 2004 In this note we analyze the relationship between one-step ahead prediction errors and interpolation errors in time series. We obtain an expression of the prediction errors in terms of the interpolation errors and then we show that minimizing the sum of ...
Peña, Daniel, Galeano, Pedro
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TIME SERIES PREDICTION BY NEURAL NETS [PDF]
فصلنامه پژوهشهای اقتصادی ایران, 2002 Application of non-classical methods in modeling complex systems and forecasting their behavior has become as more as usual for the scientists and professionals.
Mohammad Reza Asgari Oskoei
doaj
Bootstraping financial time series [PDF]
, 2002 It is well known that time series of returns are characterized by volatility clustering and excess kurtosis. Therefore, when modelling the dynamic behavior of returns, inference and prediction methods, based on independent and/or Gaussian observations ...
Pascual, Lorenzo +4 more
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