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Time Series Forecasting Using Hybrid CNN - RNN

version 1.0.13 (566 KB) by H Sanchez
A hybrid convolutional neural network - recurrent neural network (RNN) for time series prediction is implemented.

638 Downloads

Updated 27 May 2021

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This example aims to present the concept of combining a convolutional neural network (CNN) with a recurrent neural network (RNN) to predict the number of chickenpox cases based on previous months.
The CNN is an excellent net for feature extractions while a RNN have proved its ability to predict values in sequence-to-sequence series. At each time step the CNN extracts the main features of the sequence while the RNN learn to predict the next value on the next time step.
Please rate this contribution if you think that in some how it helps you. Thank you.

Cite As

H Sanchez (2021). Time Series Forecasting Using Hybrid CNN - RNN (https://www.mathworks.com/matlabcentral/fileexchange/91360-time-series-forecasting-using-hybrid-cnn-rnn), MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2020b
Compatible with any release
Platform Compatibility
Windows macOS Linux

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