Results 21 to 30 of about 80,914 (224)
Gated Orthogonal Recurrent Units: On Learning to Forget [PDF]
Neural Computation, 2019 We present a novel recurrent neural network (RNN)–based model that combines the remembering ability of unitary evolution RNNs with the ability of gated RNNs to effectively forget redundant or irrelevant information in its memory. We achieve this by extending restricted orthogonal evolution RNNs with a gating mechanism similar to gated recurrent unit ...
Li Jing 0001 +6 more
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Highway Speed Prediction Using Gated Recurrent Unit Neural Networks
Applied Sciences, 2021 Movement analytics and mobility insights play a crucial role in urban planning and transportation management. The plethora of mobility data sources, such as GPS trajectories, poses new challenges and opportunities for understanding and predicting ...
Myeong-Hun Jeong +3 more
doaj +1 more source
Gated Recurrent Unit Network-Based Short-Term Photovoltaic Forecasting
Energies, 2018 Photovoltaic power has great volatility and intermittency due to environmental factors. Forecasting photovoltaic power is of great significance to ensure the safe and economical operation of distribution network.
Yusen Wang, Wenlong Liao, Yuqing Chang
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A simple gated recurrent network for detection of power quality disturbances
IET Generation, Transmission & Distribution, 2021 This paper presents a new concise deep learning–based sequence model to detect the power quality disturbances (PQD), which only uses original signals and does not require pre‐processing and complex artificial feature extraction process.
Xiangrong Zu, Kai Wei
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PERBANDINGAN MODEL LSTM DAN GRU UNTUK MEMPREDIKSI HARGA MINYAK GORENG DI INDONESIA
Edusaintek, 2022 Cooking oil, a food ingredient used for cooking, has increased in price in Indonesia. Based on the Indonesian Strategic Food Price Center data, cooking oil reached twice the regular price at the beginning of 2022.
Mochammad Agus Sholeh
doaj +1 more source
Improving Speech Recognition by Revising Gated Recurrent Units [PDF]
Interspeech 2017, 2017 Speech recognition is largely taking advantage of deep learning, showing that substantial benefits can be obtained by modern Recurrent Neural Networks (RNNs). The most popular RNNs are Long Short-Term Memory (LSTMs), which typically reach state-of-the-art performance in many tasks thanks to their ability to learn long-term dependencies and robustness ...
Mirco Ravanelli +3 more
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Robust constrained nonlinear Model Predictive Control with Gated Recurrent Unit model - Extended version [PDF]
at - Automatisierungstechnik, 2023 In this paper we propose a robust Model Predictive Control where a Gated Recurrent Unit network model is used to learn the input-output dynamic of the system under control.
I. Schimperna, L. Magni
semanticscholar +1 more source
IEEE Access, 2019 This paper investigates variant-gated recurrent units with encoders to preprocess packets for payload-aware intrusion detection. The variant-gated recurrent units include an encoded gated recurrent unit (E-GRU) and an encoded binarized gated recurrent ...
Yiran Hao, Yiqiang Sheng, Jinlin Wang
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IEEE Access, 2023 Recurrent Neural Networks (RNNs) and their variants have been demonstrated tremendous successes in modeling sequential data such as audio processing, video processing, time series analysis, and text mining.
Tariq Ahmad +5 more
semanticscholar +1 more source
Attention-Based Pose Sequence Machine for 3D Hand Pose Estimation
IEEE Access, 2020 Most of the existing methods for 3D hand pose estimation are performed from a single depth map. In that case, the depth missing challenges from input frames caused by hand self-occlusions and imaging quality lead to multi-valued mapping phenomenon and ...
Fangtai Guo +4 more
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