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使用实验数据和智能模型,预测通透路面的排水特性
Alireza Rezaei1, Hojat Karami2
1Civil Engineering Department, Semnan University, Semnan, Iran.
Environmental science and pollution research international
|August 15, 2024
概括
该SVM-BA模型准确地预测了透性路面的下水,其性能优于SVM-GOA和SVM. 这种智能算法对于在透互锁混凝土路面 (PICP) 和耐堵透路面 (CRP) 中管理降雨-流水关系至关重要.
科学领域:
- 环境工程 环境工程
- 水文学的水文学
- 可持续的路面设计
背景情况:
- 穿透性路面越来越多地使用,需要准确的流水预测.
- 由于数据的变化和非线性动态,预测降雨-流水关系是复杂的.
- 智能算法为模拟这些复杂的水文过程提供解决方案.
研究的目的:
- 调查透气互锁混凝土路面 (PICP) 和高强度阻塞性透气路面 (CRP) 的排水控制参数.
- 为了比较支持矢量机 (SVM),SVM-Bat (SVM-BA) 和SVM-Grasshopper (SVM-GOA) 算法在预测流水特征方面的性能.
- 确定最有效的智能算法,用于在透性路面系统中预测流水.
主要方法:
- 使用SVM,SVM-BA和SVM-GOA算法进行下游预测.
- 输入变量包括路面覆盖率,降雨强度,斜率和路面类型系数.
- 输出变量是排水系数,排水时间和峰值排放,基于86个训练和22个测试数据点.
主要成果:
- SVM-BA模型表现出卓越的性能,实现了最低的平均绝对误差 (MAE) 预测排水系数 (0.010),排水时间 (1.330分钟) 和峰值放电 (0.029升/分钟).
- SVM-GOA排名第二,MAE值为0.051 (C),3.285分钟 (Tr) 和0.097升/分钟 (Qp).
- 标准SVM模型显示了最弱的性能,MAE值为0.063 (C),4.470分钟 (Tr) 和0.121升/分钟 (Qp).
结论:
- SVM-BA算法是最有效的用于预测透路面的排水特性.
- 智能算法,特别是SVM-BA,可以在PICP和CRP中成功模拟复杂的降雨-流水动态.
- 研究结果支持使用先进的计算方法来优化通透路面的设计和性能.
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