IET Generation, Transmission & Distribution, 2023 Numerous studies on short‐term load forecasting (STLF) have used feature extraction methods to increase the model's accuracy by incorporating multidimensional features containing time, weather and distance information.
Shiyan Yi +4 more
doaj +1 more source
Brain inspired neuronal silencing mechanism to enable reliable sequence identification
Scientific Reports, 2022 Real-time sequence identification is a core use-case of artificial neural networks (ANNs), ranging from recognizing temporal events to identifying verification codes.
Shiri Hodassman +7 more
doaj +1 more source
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
doaj +1 more source
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
doaj +1 more source
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
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 +3 more sources
Fast convergence algorithm for multilayer and recurrent neural nets
, 1998 The presentation deals with a class of fast algoritms for training feedforward and recurrent neural networks, especially suited dor signal processing and ...
ORLANDI, Gianni +2 more
core +2 more sources
A hybrid model for fake news detection: Leveraging news content and user comments in fake news
IET Information Security, 2021 Nowadays, social media platforms such as Twitter have become a popular medium for people to spread and consume news because of their easy access and the rapid proliferation of news.
Marwan Albahar
doaj +1 more source
Applications of recurrent neural networks in batch reactors. Part II: Nonlinear inverse and predictive control of the heat transfer fluid temperature [PDF]
, 1998 Although nonlinear inverse and predictive control techniques based on artificial neural networks have been extensively applied to nonlinear systems, their use in real time applications is generally limited.
Zaldívar, J.M., Galván, Inés M.
core +1 more source
Less is More: Rethinking Few-Shot Learning and Recurrent Neural Nets
CoRR, 2022 Version 3 is focused exclusively on the first part of v1 and v2, correcting minor mathematical errors.
Deborah Pereg +3 more
openaire +2 more sources