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Updated: May 7, 2025

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创新的机器学习方法用于智能基础设施中的室内空气温度预测

Nataliya Shakhovska1,2, Lesia Mochurad3, Rosana Caro4

  • 1Artificial Intelligence Department, Lviv Polytechnic National University, 12 S. Bandery St, Lviv, 79013, Ukraine. nataliya.b.shakhovska@lpnu.ua.

Scientific reports
|January 3, 2025
PubMed
概括

本研究介绍了一种先进的长期短期记忆 (LSTM) 模型,具有滚动窗口交叉验证 (RWCV),用于准确的室内空气温度 (IAT) 预测,增强建筑能源管理和气候控制.

关键词:
累积错误分析 累积错误分析能源效率 能源效率是指能源的使用效率.这是LSTM的LSTM.机器学习是机器学习.智能建筑物 智能建筑物代理模拟代理模拟时间序列预测时间序列预测

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