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Gold price forecast based on LSTM-CNN model
Zhanhong He
, Junhao Zhou
,
Hong Ning Dai
, Hao Wang
Department of Computer Science
Research output
:
Chapter in book/report/conference proceeding
›
Conference proceeding
›
peer-review
52
Citations (Scopus)
Overview
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Dive into the research topics of 'Gold price forecast based on LSTM-CNN model'. Together they form a unique fingerprint.
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Keyphrases
Convolutional Neural Network Model
100%
Gold Price Forecasting
100%
Long Short-term Memory Neural Network
100%
Neural Network System
71%
Convolutional Neural Network
42%
Attention Mechanism
42%
Forecast Method
28%
Spatial Features
28%
Network Attention
28%
Attention Convolutional Neural Network
28%
Recent Advances
14%
Prediction Accuracy
14%
Excellent Performance
14%
Sentiment Analysis
14%
Encoding Method
14%
Deep Learning Methods
14%
Temporal Features
14%
Image Recognition
14%
Market Risk
14%
Risk Management
14%
Stock Selection
14%
Financial Analysis
14%
Local Patterns
14%
Recognition Analysis
14%
Gold Price
14%
Attention Weight
14%
Sequential Order
14%
Financial Forecast
14%
Selection Management
14%
Image Sentiment
14%
Econometric Techniques
14%
Computer Science
Convolutional Neural Network
100%
Neural Network Model
100%
Long Short-Term Memory Neural Network
100%
Network Component
71%
Attention (Machine Learning)
71%
Deep Learning Method
14%
Sentiment Analysis
14%
Outstanding Performance
14%
Risk Management
14%
Financial Data
14%
Economics, Econometrics and Finance
Gold Price
100%
Long Short-Term Memory Network
100%
Price Forecast
100%
Investors
14%
Pricing
14%
Risk Management
14%
Deep Learning Method
14%