Results 31 to 40 of about 428,742 (262)
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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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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Hetero-Dimensional Multitask Neuroevolution for Chaotic Time Series Prediction
IEEE Access, 2020 Chaotic time series prediction has important research and application value, and neural network-based prediction methods have problems such as low accuracy and difficulty in determining the number of nodes in the hidden layer.
Daoqing Zhang, Mingyan Jiang
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Financial time series prediction using spiking neural networks. [PDF]
PLoS ONE, 2014 In this paper a novel application of a particular type of spiking neural network, a Polychronous Spiking Network, was used for financial time series prediction.
David Reid +2 more
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Pediatric Blood &Cancer, EarlyView.ABSTRACT Background Loneliness is associated with adverse physical and mental health outcomes and remains understudied in children and adolescents undergoing cancer therapy. Pediatric oncology patients may be at increased risk due to medical isolation and disruption of social networks.
Charlotte N. Stahlfeld +5 more
wiley +1 more source
Model-Free Prediction of Multivariate Time Series
AxiomsThis paper extends a model-free prediction framework from univariate to multivariate time series. We show that, under a mild uniformly bounded first-moment condition, a multivariate time series admits a VARMA-type representation and an associated ...
Hanieh Saeidi, Adel Mohammadpour
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Adaptive Conformal Predictions for Time Series
CoRR, 2022 Uncertainty quantification of predictive models is crucial in decision-making problems. Conformal prediction is a general and theoretically sound answer. However, it requires exchangeable data, excluding time series. While recent works tackled this issue, we argue that Adaptive Conformal Inference (ACI, Gibbs and Cand{è}s, 2021), developed for ...
Zaffran, Margaux +4 more
openaire +4 more sources
Pediatric Blood &Cancer, EarlyView.ABSTRACT Rates of cancer among adolescents and young adults (AYA), age 15–39 years, are increasing. Consequently, radiation oncologists are treating more AYAs who have diagnoses spanning both pediatric and adult practices. Compared to pediatric and older adult patients, AYAs face a unique set of challenges.
Hesham Elhalawani +7 more
wiley +1 more source
Radial Basis Function Nets for Time Series Prediction [PDF]
International Journal of Computational Intelligence Systems, 2009 This paper introduces a novel ensemble learning approach based on recurrent radial basis function networks (RRBFN) for time series prediction with the aim of increasing the prediction accuracy. Standing for the base learner in this ensemble, the adaptive
Abdelhamid Bouchachia
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