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Arxiv
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M2WLLM: Multi-Modal Multi-Task Ultra-Short-term Wind Power Prediction Algorithm Based on Large Language Model
- The study introduces M2WLLM, a model that utilizes Large Language Models (LLMs) for ultra-short-term wind power forecasting.
- M2WLLM combines textual information and numerical data to improve wind power forecasting accuracy through multi-modal data integration.
- The model includes a Prompt Embedder and a Data Embedder to effectively fuse prompts and numerical inputs within the LLMs framework.
- Empirical evaluations on wind farm data from Chinese provinces show that M2WLLM outperforms existing methods like GPT4TS in accuracy and few-shot learning capabilities.
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