Results 31 to 40 of about 1,891,060 (279)
Recurrent Neural Networks Applied to GNSS Time Series for Denoising and Prediction [PDF]
, 2019 Global Navigation Satellite Systems (GNSS) are systems that continuously acquire data and provide position time series. Many monitoring applications are based on GNSS data and their efficiency depends on the capability in the time series analysis to ...
Cascarano, Pasquale +5 more
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Poster: Visual prediction of time series [PDF]
2009 IEEE Symposium on Visual Analytics Science and Technology, 2009 Many well-known time series prediction methods have been used daily by analysts making decisions. To reach a good prediction, we introduce several new visual analysis techniques of smoothing, multi-scaling, and weighted average with the involvement of human expert knowledge. We combine them into a well-fitted method to perform prediction.
Hao, Ming +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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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
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Time series prediction evolving Voronoi regions [PDF]
Applied Intelligence, 2009 Time series prediction is a complex problem that consists of forecasting the future behavior of a set of data with the only information of the previous data. The main problem is the fact that most of the time series that represent real phenomena include local behaviors that cannot be modelled by global approaches.
Luque, Cristóbal +2 more
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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
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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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Forecasting time series by means of evolutionary algorithms [PDF]
, 2004 Proceeding of: 8th International Conference in Parallel Problem Solving from Nature - PPSN VIII , Birmingham, UK, September 18-22, 2004.The time series forecast is a very complex problem, consisting in predicting the behaviour of a data series with only ...
C.Z. Janikow +8 more
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Long Short-Term Memory Prediction for COVID19 Time Series
Telfor Journal, 2021 Entire world has been dealing with the number of new Coronavirus 2 or COVID-19 cases. The spread of this severe acute respiratory syndrome has produced many concerns worldwide.
M. S. Milivojević, A. Gavrovska
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Sequential Quantile Prediction of Time Series [PDF]
IEEE Transactions on Information Theory, 2011 Motivated by a broad range of potential applications, we address the quantile prediction problem of real-valued time series. We present a sequential quantile forecasting model based on the combination of a set of elementary nearest neighbor-type predictors called "experts" and show its consistency under a minimum of conditions.
Biau, Gérard, Patra, B.
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