Dual-LSTM混合模型时序数据多步预测智能化生产线设备健康状态,加工过程状态,产品信息等数据具有复杂化,多样化,大容量的特点,传统上对于设备的运行状况主要依靠人工经验来判断,不能及时有效地给出维护意见.针对上述问题,本文提出了一种基于Dual-LSTM(Long Short-Term M emory)混合模型的时序数据预测方法.首先建立LSTM预测...
cell_r= tf.nn.rnn_cell.LSTMCell(hparams.rnn_dim,forget_bias = 2.0,use_peepholes=True,state_is_tuple=True) output_ques, state_ques= tf.nn.bidirectional_dynamic_rnn(cell, cell_r, ques_1, sequence_length = ques_len, dtype =tf.float32) with tf.variable_scope('rnn_ques2') as vs_qu...
由于基线模型在挑战中无法访问,一个额外的基线系统被训练来量化堆叠网络的性能,与使用时频屏蔽的连续LSTM层模型相比。该模型有四个连续的LSTM层,每个层有512个单元,然后是一个完全连接的部分,通过sigmoid激活来预测TF-mask。模型的输入等于DTLN-AEC模型的第一个分离核。掩模与近端传声器信号的非规格化幅度相乘,然后转...
Dual LSTM Encoder for Dialog Response Generation. Contribute to dennybritz/chatbot-retrieval development by creating an account on GitHub.
LogLS: Research on System Log Anomaly Detection Method Based on Dual LSTM. Symmetry. 2022; 14(3):454. https://doi.org/10.3390/sym14030454 Chicago/Turabian Style Chen, Yiyong, Nurbol Luktarhan, and Dan Lv. 2022. "LogLS: Research on System Log Anomaly Detection Method Based on Dual ...
In this paper, we present a reverberation removal approach for speaker verification, utilizing dual-label deep neural networks (DNNs). The networks perform feature mapping between the spectral features of reverberant and clean speech. Long short term memory recurrent neural networks (LSTMs) are ...
We firstly build two models, unidirectional dual-layer LSTM model and bidirectional LSTM model, which aim to predict the average daily prices of Bitcoin after 1 day based on the prices in the previous 8 days. We compare the forecast results for different size time windows for the prices ...
In this paper, we present a reverberation removal approach for speaker verification, utilizing dual-label deep neural networks (DNNs). The networks perform feature mapping between the spectral features of reverberant and clean speech. Long short term memory recurrent neural networks (LSTMs) are traine...
LSTM-autoencoder with attentions for multivariate time seriesThis repository contains an autoencoder for multivariate time series forecasting. It features two attention mechanisms described in A Dual-Stage Attention-Based Recurrent Neural Network for Time Series Prediction and was inspired by Seanny123's ...
基于层叠式残差 LSTM 网络的 桥梁非线性地震响应预测 A data-driven deep learning method using the stacked residual long short-term memory network (ResLSTM) is proposed to predict bridge seismic responses. The... 廖聿宸,张瑞阳,林榕,... - 《Engineering Mechanics / Gongcheng Lixue》 被引量: 0...