Multi-dimensional time sequence prediction system and method based on deep learning
The invention provides a multi-dimensional time sequence prediction system and method based on deep learning, the multi-dimensional time sequence prediction system based on deep learning comprises a data acquisition module, a multi-head jump loop network model training module and a prediction verifi...
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Main Authors | , , , , , |
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Format | Patent |
Language | Chinese English |
Published |
29.03.2024
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Subjects | |
Online Access | Get full text |
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Summary: | The invention provides a multi-dimensional time sequence prediction system and method based on deep learning, the multi-dimensional time sequence prediction system based on deep learning comprises a data acquisition module, a multi-head jump loop network model training module and a prediction verification module, and the data acquisition module is used for acquiring multi-dimensional time sequence data; the multi-head jump loop network model training module comprises a one-dimensional convolution layer, a multi-head jump loop module, a multi-head jump convolution module, a fusion feature module and a prediction verification module, uses an autoregression layer to take original time sequence data as input, and fuses outputs of a dense layer and the autoregression layer to obtain a multi-head jump loop network model; according to the method, compared with a traditional autoregression prediction method, the medium-and-long-term prediction effect is more accurate, and compared with other light time sequence predi |
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Bibliography: | Application Number: CN202311799809 |