Results 11 to 20 of about 1,858,056 (293)
A multivariate natural gas load forecasting method based on residual recurrent neural network
Electronics Letters, 2023 Current natural gas load forecasting encounters with the conundrum of unsatisfying accuracy and interpretability. To address the challenge, a multi‐variate forecasting method is proposed, which contains three phases: First, an integrate history‐climate ...
Xueqing Ni +3 more
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Enhanced road information representation in graph recurrent network for traffic speed prediction
IET Intelligent Transport Systems, 2023 Correctly capturing the spatial‐temporal correlation of traffic sequences will benefit to make accurate predictions of the future traffic states. In the paper, the methods of enhancing road spatial and temporal information representation are proposed ...
Lei Chang +4 more
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A feed forward neural network approach for matrix computations [PDF]
, 2001 This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.A new neural network approach for performing matrix computations is presented. The idea of this approach is to construct a feed-forward neural network (FNN)
Al-Mudhaf, Ali F
core +7 more sources
On Learning Interpreted Languages with Recurrent Models
Computational Linguistics, 2022 Can recurrent neural nets, inspired by human sequential data processing, learn to understand language? We construct simplified data sets reflecting core properties of natural language as modeled in formal syntax and semantics: recursive syntactic ...
Denis Paperno
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Comparing Human Activity Recognition Models Based on Complexity and Resource Usage
Applied Sciences, 2021 Human Activity Recognition (HAR) is a field with many contrasting application domains, from medical applications to ambient assisted living and sports applications.
Simon Angerbauer +3 more
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Attention‐based novel neural network for mixed frequency data
CAAI Transactions on Intelligence Technology, 2021 It is a common fact that data (features, characteristics or variables) are collected at different sampling frequencies in some fields such as economic and industry.
Xiangpeng Li +3 more
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Learning Recurrent Neural Net Models of Nonlinear Systems
CoRR, 2020 15 pages; previous versions, including the one in Proc. L4DC 2021, had an error in Theorem 3.1, which propagated to the main result (Theorem 3.2)
Joshua Hanson +2 more
openaire +3 more sources
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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CAAI Transactions on Intelligence Technology, 2021 A special recurrent neural network (RNN), that is the zeroing neural network (ZNN), is adopted to find solutions to time‐varying quadratic programming (TVQP) problems with equality and inequality constraints.
Xiaoyan Zhang +5 more
doaj +1 more source
Mack-Net model: Blending Mack’s model with Recurrent Neural Networks
Expert Systems with Applications, 2022 In general insurance companies, a correct estimation of liabilities plays a key role due to its impact on management and investing decisions. Since the Financial Crisis of 2007-2008 and the strengthening of regulation, the focus is not only on the total reserve but also on its variability, which is an indicator of the risk assumed by the company. Thus,
Eduardo Ramos-Pérez +2 more
openaire +4 more sources