Tourism Demand Forecasting Based on an LSTM Network and Its Variants
The need for accurate tourism demand forecasting is widely recognized. The unreliability of traditional methods makes tourism demand forecasting still challenging. Using deep learning approaches, this study aims to adapt Long Short-Term Memory (LSTM), Bidirectional LSTM (Bi-LSTM), and Gated Recurren...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-08-01
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| Series: | Algorithms |
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| Online Access: | https://www.mdpi.com/1999-4893/14/8/243 |