We describe the standard Gated Recurrent Unit (GRU) in recurrent neural networks (RNNs) as was originally introduced. Next, by adopting the same notations as for LSTMs in the previous chapter, we directly show how it can viewed as a reduced form of the LSTM RNNs . Then, we explore ...
In this study, we propose a model that combines the advantages of Convolutional layers, Gated Recurrent Unit (GRU) networks, and Multi-Head Attention Mechanism (MHA) to create the ConvolGRU-MHA fusion model, as shown in Fig. 1. First, the input channel is amplified by the convolution layer...
英文摘要: Accurate and real-time traffic flow forecasting is of great significance to trafficplanning,traffic management and traffic control.However,traffic flowforecasting remains challenging owing to the constraints of the road networktopology and the spatial-temporal correlation of traffic flow with time...
首次系统地检测了RNN架构以及RNN与CNN和传统的基于特征的关系抽取方法相结合的工作,本文采用LSTM网络的一种变体GRU(Gated Recurrent Unit)展开实验,同时,首次提出了融合CNN和RNN网络的三种不同的方式:Ensembling(集成)、Stacking(堆叠)、Voting(投票),提高了关系抽取的精确度。
By focusing on the input optimization of the network, this study develops a novel wind speed forecasting system based on a deep learning gated recurrent unit (GRU) network. Specifically, to begin with, the Pearson correlation, the partial correlation, and the maximum information coefficient analyses...
让各个门层也接受细胞状态输入的peephole connection: coupled 忘记和输入门: Gated Recurrent Unit (GRU): 将忘记门和输入门合成了一个单一的 更新门。同样还混合了细胞状态和隐藏状态,和其他一些改动。最终的模型比标准的 LSTM 模型要简单,也是非常流行的变体。
Each recurrent layer has two sets of weights: one for the input and the second for the hidden unit. The last feedforward layer, which computes the final output for the kth time step, is just like an ordinary layer of a traditional feedforward network. The Activation Function We can us...
The paper concludes that Gated Recurrent Unit (GRU) (used for labeling) together with the FURIA algorithm (used for rule extraction) obtain the best results in their experiments. The comparison made in their paper is certainly of high academic value. However, the proposal requires an enormous ...
Traffic flow prediction using bi-directional gated recurrent unit method (基于双向GRU方法的交通流预测) Shengyou Wang, Chunfu Shao, Jie Zhang, Yan Zheng & Meng Meng 链接:https://doi.org/10.1007/s44212-022-00015-z Geo-fence planning for dockless bike-sharing systems: a GIS-based multi-criteri...
at Google. At the time, recurrent neural networks (RNNs), such as Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU), were the go-to choice for sequence modeling tasks. However, RNNs had several limitations in processing long-range dependencies and parallelization. The Transformer ...