一个改进的加权平均算法与基于云的风险意识的随机模型用于建筑能源优化
Suraparb Keawsawasvong1, Thira Jearsiripongkul2, Mohammad Khajehzadeh3
1Research Unit in Sciences and Innovative Technologies for Civil Engineering Infrastructures, Department of Civil Engineering, Thammasat School of Engineering, Thammasat University, Pathumthani, 12120, Thailand.
Scientific reports
|November 27, 2025
概括
本研究介绍了一种基于云计算理论的模型,用于优化建筑能耗,使用改进的加权平均算法 (IWAA) 来最大限度地降低年度能耗 (AEC),同时考虑到效率的不确定性.
科学领域:
- 建筑能效优化 建筑能效优化
- 随机模型的建模
- 云理论应用 云理论应用
背景情况:
- 建筑的能源消耗是全球能源使用的一个重要因素.
- 冷却和加热效率的不确定性对能源优化构成风险.
- 现有的优化算法可能无法充分处理参数变化.
研究的目的:
- 开发基于云理论的随机模型,用于建筑能源优化.
- 通过解决环境参数变化,最大限度地降低办公楼的年度能源消耗 (AEC).
- 引入一个改进的加权平均算法 (IWAA) 与一个动态加权更新机制.
主要方法:
- 提出了一个基于云理论的随机模型.
- 开发了带有动态权重更新机制的改进权重平均算法 (IWAA).
- 在不同天气条件下对IWAA与基准函数以及建筑能源优化场景进行了评估.
主要成果:
- 与WAA,PSO和WOA相比,IWAA表现优越,在较低的AEC中产生更稳定和更一致的结果.
- 通过云理论将不确定性纳入,提高了能源预测的现实性和可信性.
- 该模型有效地平衡了勘探-开采权衡,以提高优化.
结论:
- 拟议的IWAA提供了一个强有力的方法来构建能源优化,有效地管理不确定性.
- 云理论集成提高了动态环境中能源预测的可靠性.
- 开发的模型显示了可持续和节能建筑设计的巨大潜力.
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