Results 31 to 40 of about 411,481 (262)
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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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
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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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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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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Personalized Zebrafish Models for Fusion‐Positive Pediatric Sarcomas
Pediatric Blood &Cancer, EarlyView.ABSTRACT Clinical sequencing efforts have revolutionized our approaches to categorizing pediatric cancers in real time. This has dramatically improved our ability to profile pediatric tumors, identify actionable vulnerabilities, and influence clinical care.
Lisa H. Hall +2 more
wiley +1 more source
The Role of “Adult‐Onset” Cancer Predisposition Genes in Pediatric Cancer: A Comprehensive Review
Pediatric Blood &Cancer, EarlyView.ABSTRACT Current literature estimates that 10% of pediatric cancers are caused by pathogenic or likely pathogenic (P/LP) germline variants in cancer predisposition genes (CPGs). Variants in CPGs thought to increase cancer risk exclusively during adulthood are referred to as “adult‐onset” CPGs (aoCPGs).
Maria Rozo +5 more
wiley +1 more source
Multivariate time series prediction based on ARCLSTM
Journal of Measurement Science and Instrumentation, 2021 Time series is a kind of data widely used in various fields such as electricity forecasting, exchange rate forecasting, and solar power generation forecasting, and therefore time series prediction is of great significance.
QIAO Gangzhu, SU Rong, ZHANG Hongfei
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