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About Time Series Forecasting Using Deep Learning - MATLAB & Simulink
This document describes how to forecast time series data using a long short-term memory (LSTM) neural network. It uses a dataset of monthly chickenpox cases to train an LSTM network to predict future cases based on previous months. The network is trained on 90% of the data and tested on the remaining 10%. Forecasts are made both by predicting each future time step and by updating the network state with each new observed value. Updating with observations improves forecast accuracy.
Detailed Information
| Author: | ['Ali Algargary'] |
|---|---|
| Publication Year: | 2019 |
| Pages: | 6 |
| Language: | English |
| Format: | |
| Price: | FREE |
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