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long short-term memory neural network

Prediction Of Stock Trend For Swing Trades Using Long Short-Term Memory Neural Network Model

Prediction Of Stock Trend For Swing Trades Using Long Short-Term Memory Neural Network Model

... each memory cell of LSTM ...the Long Short-Term Memory Neural Network for the stock ...the long term predictions rather than intraday or for few days which ...

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Multi Timescale Long Short Term Memory Neural Network for Modelling Sentences and Documents

Multi Timescale Long Short Term Memory Neural Network for Modelling Sentences and Documents

... recurrent neural network (RNN) (Mikolov et ...a long-term memory of sentences as op- posed to the short-memory in ...

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Keyword Spotting with Long Short term Memory Neural Network Architectures

Keyword Spotting with Long Short term Memory Neural Network Architectures

... neutral network (DNN) models [1], which realize the speech recognition by calculating the emission probability of HMM model in its complicated networks, have a good performance in keyword spotting ...Recurrent ...

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UWB at IEST 2018: Emotion Prediction in Tweets with Bidirectional Long Short Term Memory Neural Network

UWB at IEST 2018: Emotion Prediction in Tweets with Bidirectional Long Short Term Memory Neural Network

... This paper describes our system created for the WASSA 2018 Implicit Emotion Shared Task. The goal of this task is to predict the emo- tion of a given tweet, from which a certain emotion word is removed. The removed word ...

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Long Short Term Memory Neural Networks for Chinese Word Segmentation

Long Short Term Memory Neural Networks for Chinese Word Segmentation

... a neural model based on Long Short-Term Memory Neural Network (LSTM) (Hochreiter and Schmid- huber, 1997) that explicitly model the previous information by exploiting ...

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The Research of Low Earth Orbit Prediction of Satellite Based on Deep Neural Network

The Research of Low Earth Orbit Prediction of Satellite Based on Deep Neural Network

... deep neural network in satellite orbit prediction, the long short-term memory neural network prediction is carried out based on the actual data of X, Y and Z ...

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Disfluency Detection using a Noisy Channel Model and a Deep Neural Language Model

Disfluency Detection using a Noisy Channel Model and a Deep Neural Language Model

... a long short-term memory neural network language model to rescore the candidate disfluency analyses produced by a noisy channel ...

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Aspect specific Sentiment Classification Method Based on High dimensional Representation

Aspect specific Sentiment Classification Method Based on High dimensional Representation

... years, neural networks have gradually shown their superiority in the field of sentiment analysis, such as recurrent neural ...a long short term memory neural ...

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Efficient power component identification with long short-term memory and deep neural network

Efficient power component identification with long short-term memory and deep neural network

... With the rapid development of artificial intelligence, live working robots that can perform automatic inspection have received extensive attention from major power grid corporations [1]. For power systems, blackouts mean ...

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Route Intrusion Detection Based on Long Short Term Memory Recurrent Neural Network

Route Intrusion Detection Based on Long Short Term Memory Recurrent Neural Network

... Internet, network security is the key point of the current research of computer ...the network to forward data ...a Long Short Term Memory (LSTM) architecture applied to the ...

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Prediction of Multi Currency Exchange Rates Using Deep Learning

Prediction of Multi Currency Exchange Rates Using Deep Learning

... Abstract: Predicting multi-currency exchange rates and processing time series information is often a significant issue in the economic market. This paper offers the prediction of top traded currencies in the world using ...

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Stock Market Cost Forecasting by Recurrent Neural Network on Long Short Term Memory Model

Stock Market Cost Forecasting by Recurrent Neural Network on Long Short Term Memory Model

... Recurrent neural network single cell architecture In the above image, Xt is the current input, ht-1 is the previous hidden state, Xt-1 is previous ...

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Image Description using Deep Neural Networks

Image Description using Deep Neural Networks

... the network. Convolutional Neural Networks (CNNs) are deployed for visual feature extraction and recursive neural network based architectures, either a simple recursive network or a ...

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Unified Framework For Deep Learning Based Text Classification

Unified Framework For Deep Learning Based Text Classification

... artificial neural networks, which are inspired by biological brain model made of ...of term ―deep‖ in deep learning is that there are more multiple hidden layers before the output is performed through ...

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A Neural Conversational Model for Automatic Generation of Conversations

A Neural Conversational Model for Automatic Generation of Conversations

... (Long Short Term Memory) [13] based neural network which takes the word embedding’s of the input and converts them to a thought ...LSTM Network are randomly initialized in ...

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Sentiment on Twitter Data Set using Recurrent Neural Network   Long Short Term Memory

Sentiment on Twitter Data Set using Recurrent Neural Network Long Short Term Memory

... Recurrent Neural Networks - Long Short Term Memory and ...evaluated. Long Short Term Memory classification algorithm is applied to classify the tweets into ...

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Machine-learning-assisted correction of correlated qubit errors in a topological code

Machine-learning-assisted correction of correlated qubit errors in a topological code

... ing, neural networks are a promising new ap- proach to quantum error ...recurrent neural network can be trained, using only experimental ly accessible data, to detect errors in a widely used topo- ...

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It may be time to perfect the neuron of artificial neural network

It may be time to perfect the neuron of artificial neural network

... a network focusing on spatial information [CNN, the representative field is computer vision ...a network focusing on temporal information [RNN, the representative field is natural language processing ...

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Long Short Term Memory Recurrent Neural Network Architectures

Long Short Term Memory Recurrent Neural Network Architectures

... Quickly explaining the information of a picture may be considered a essential disadvantage in design technology that attaches pc perspective and language method. In that report, we have got an inclination to surprise a ...

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Deep Learning For Anticipation Of Cardiovascular Disease: A Practical Approach

Deep Learning For Anticipation Of Cardiovascular Disease: A Practical Approach

... Artificial Neural Network (ANN) Multilayer Perceptron, (Recurrent Neural NetworkLong Short Term Memory (RNN- LSTM) and Independent RNN (IndRNN) classifiers to ...

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