Results 11 to 20 of about 37,616 (181)
Multicategory choice modeling by recurrent neural nets
Journal of Retailing and Consumer ServicesIn multicategory choice, a customer may purchase multiple products or product categories at the same time. Hidden variables of recurrent nets depend on current inputs and hidden variables of the previous period. We investigate the three main variants of recurrent neural nets, which we compare to multilayer perceptrons and multivariate logit models ...
Harald Hruschka
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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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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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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
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IET Software, 2021 Source code suggestion is the utmost helpful feature in the integrated development environments that helps to quicken software development by suggesting the next possible source code tokens.
Yasir Hussain, Zhiqiu Huang, Yu Zhou
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Automatic Synthesis of Neurons for Recurrent Neural Nets
, 2022 We present a new class of neurons, ARNs, which give a cross entropy on test data that is up to three times lower than the one achieved by carefully optimized LSTM neurons. The explanations for the huge improvements that often are achieved are elaborate skip connections through time, up to four internal memory states per neuron and a number of novel ...
Olsson, Roland +2 more
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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 ...
Bitzer, S., Kiebel, S.
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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
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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
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