预测城市建筑垃圾产生利用TI-TSTLNGM(1,1) 基于COOT算法模型
Wanling Zhu1,2, Hao Cui1,2
1College of Civil Engineering, Jiangxi Science and Technology Normal University, Nanchang, People's Republic of China.
Environmental technology
|June 3, 2025
概括
本研究引入了一种增强的灰色模型,以准确预测建筑垃圾 (C&W) 的产生. 这种新的方法提高了预测准确度,以更好地规划废物管理.
科学领域:
- 环境科学 环境科学
- 土木工程 土木工程是指土木工程.
- 数据科学数据科学数据科学
背景情况:
- 由于数据的波动性和不完整性,准确估计建筑垃圾 (C&W) 生产趋势具有挑战性.
- 现有的预测方法往往缺乏有效废物管理规划所需的精度.
研究的目的:
- 开发一种新的预测方法和一个增强的灰色模型,用于科学估计和预测C&W代.
- 提高C&W生成预测的准确性和可靠性,以便更好地规划和制定废弃物处理政策.
主要方法:
- 转换初始序列并纳入三参数间隔灰色数字来处理数据问题.
- 将三参数间隔的灰色数字与废物生成系数集成,以精确确定C&W范围.
- 使用COOT算法优化时间滞后系数,以提高预测准确度.
主要成果:
- 与传统的灰色预测和指数级光滑方法相比,增强的灰色模型表现出卓越的性能.
- 该模型为C&W生成预测提供了更准确,更可靠的范围.
- 广州的案例研究证实了该模型的有效性和适用性.
结论:
- 这种新的预测方法为区域建筑废物处理,处置和资源分配提供了科学基础.
- 该研究为C&W处置规划和政策制定提供了关键的参考值.
- 增强的灰色模型为C&W管理提供了合理,适用和有效的解决方案.
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