Agent-Based ML-LLM Fusion with Self-Optimizing Prompts for Plateau Weather Alerts
To address insufficient contextualization, weak generalization, and poor scenario adaptation in tourism meteorological services, we propose SmartWeatherAgent--a unified three-stage architecture integrating intent recognition, hazard prediction, and reasoning-enhanced generation. The system fuses rule-based methods with large language models to parse queries at multiple granularities and employs a LightGBM model enriched with highland-specific features (e.g., wind speed abruptness rate), achieving an F1-Macro score of 0.605 with 1.60 ms latency on high-wind, precipitation, and low-temperature events. A 12-round micro-step prompt self-optimization loop boosts the composite warning quality s...
| Authors | Shuai Yan, Yang Xu, Shan He |
|---|---|
| Primary category | cs.AI |
| Published | 9 September 2026 |
| Last updated at source | 9 September 2026 |
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