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English(EN) Large Language Models for HVAC Operations in Building Energy Systems: A Critical Review of Methods, Applications, and Deployment Readiness

LLM 在暖通空调方面展现出潜力,但尚未准备好被行业采纳

对 2023 年至 2026 年 3 月期间发表的 66 项研究进行的最新审查表明,尽管大型语言模型 (LLM) 在建筑能源系统的暖通空调运营方面展现出潜力,但它们尚未准备好被广泛的行业采纳。该研究主要关注建筑能源建模,在负荷预测方面进展有限。目前,LLM 最适合语义和工作流任务,例如点名称规范化和操作员支持,而不是自主控制,后者仍然依赖于传统的机器学习和模型预测控制方法。 AI

影响 目前,LLM 最适合建筑能源系统的语义和工作流任务,而不是自主控制。

排序理由 该集群包含一篇经过同行评审的学术论文,详细介绍了对现有研究的系统性审查。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

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LLM 在暖通空调方面展现出潜力,但尚未准备好被行业采纳

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该集群包含一篇经过同行评审的学术论文,详细介绍了对现有研究的系统性审查。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.AI TIER_1 English(EN) · Alexander Neubauer, Tianzhen Hong, Han Li, Mengbo Yu, Amin Darbandi, Yannick F\"urst, Martin Kriegel ·

    用于楼宇能源系统暖通空调运行的大型语言模型:方法、应用和部署就绪情况的批判性回顾

    arXiv:2609.05314v1 Announce Type: new Abstract: Building automation systems generate rich sensor data yet remain insight-poor because heterogeneous point naming, missing metadata, and fragmented documentation obstruct their operational use. This systematic review analyses and cod…