Forecasting Method based upon GRU-based Deep Learning Model

2020 International Conference on Computational Science and Computational Intelligence (CSCI)(2020)

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摘要
In this research, the world model has a modified RNN model carried out by a bi-directional gated recurrent unit (BGRU) as opposed to a traditional long short-term memory (LSTM) model. BGRU tends to use less memory while executing and training faster than an LSTM, as it uses fewer training parameters. However, the LSTM model provides greater accuracy with datasets using longer sequences. Based upon...
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关键词
Training,Deep learning,Scientific computing,Computational modeling,Memory management,Bidirectional control,Logic gates
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