TourismNeuro xLSTM: neuro-inspired xLSTM for rural tourism planning and innovation
The model's ability to process complex data dependencies and deliver precise predictions makes it a valuable tool for rural tourism planners, offering actionable insights that can enhance strategic decision-making and resource allocation.
Authors
- Jing Jiang (ORCID: https://orcid.org/0000-0001-5301-7779)
- You Li (ORCID: https://orcid.org/0000-0002-2246-9366)
Institutions
- United States Department of Housing and Urban Development (US)
- Ministry of Housing and Urban-Rural Development (CN)
- Sichuan Tourism University (CN)
- Southwest Jiaotong University (CN)
Publication Details
- Journal
- Frontiers in Computational Neuroscience
- Published
- 2025-04-08
- DOI
- https://doi.org/10.3389/fncom.2025.1495313
- Citations
- 1
- Primary Topic
- Energy Load and Power Forecasting
- Type
- article
- Field-Weighted Citation Impact
- 0.73