Results 21 to 30 of about 2,008,811 (296)
Deep learning for time series forecasting: The electric load case
CAAI Transactions on Intelligence Technology, 2022 Management and efficient operations in critical infrastructures such as smart grids take huge advantage of accurate power load forecasting, which, due to its non‐linear nature, remains a challenging task.
Alberto Gasparin +2 more
doaj +1 more source
Applications of recurrent neural networks in batch reactors. Part I: NARMA modelling of the dynamic behaviour of the heat transfer fluid [PDF]
, 1997 This paper is focused on the development of nonlinear models, using artificial neural networks, able to provide appropriate predictions when acting as process simulators. The dynamic behaviour of the heat transfer fluid temperature in a jacketed chemical
J.M. Zaldı́var +3 more
core +1 more source
SORN : a self-organizing recurrent neural network [PDF]
, 2009 Understanding the dynamics of recurrent neural networks is crucial for explaining how the brain processes information. In the neocortex, a range of different plasticity mechanisms are shaping recurrent networks into effective information processing ...
Pipa, Gordon +5 more
core +1 more source
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
Sensors, 2021 Recording human gestures from a wearable sensor produces valuable information to implement control gestures or in healthcare services. The wearable sensor is required to be small and easily worn.
Edwin Valarezo Añazco +5 more
doaj +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
IET Smart Grid, 2022 The automated identification and localisation of grid disturbances is a major research area and key technology for the monitoring and control of future power systems.
André Kummerow +2 more
doaj +1 more source
Graphical Analysis of the Progression of Atrial Arrhythmia Using Recurrent Neural Networks
International Journal of Computational Intelligence Systems, 2020 Pacemaker logs are used to predict the progression of paroxysmal cardiac arrhythmia to permanent atrial fibrillation by means of different deep learning algorithms. Recurrent Neural Networks are trained on data produced by a generative model.
Nahuel Costa +3 more
doaj +1 more source
Cross refinement network with edge detection for salient object detection
IET Signal Processing, 2021 Salient object detection aims to identify the most attractive objects from images. However, their boundaries are typically of poor quality when predicted using available methods.
Junjiang Xiang +4 more
doaj +1 more source
Recognizing recurrent neural networks (rRNN): Bayesian inference for recurrent neural networks [PDF]
Biological Cybernetics, 2012 Recurrent neural networks (RNNs) are widely used in computational neuroscience and machine learning applications. In an RNN, each neuron computes its output as a nonlinear function of its integrated input. While the importance of RNNs, especially as models of brain processing, is undisputed, it is also widely acknowledged that the computations in ...
Sebastian Bitzer, Stefan J. Kiebel
openaire +4 more sources