基于遗传算法的水质模型参数估计研究
Research on Parameter Estimation of Water Quality Models Based on Genetic Algorithm
王远飞1
作者信息
- 1. 中国建筑西南设计研究院有限公司,四川成都 610041
- 折叠
摘要
氯是用于维持配水管网水质最常见的消毒剂,但其浓度受到严格的限制,其浓度应足以去除配水管网中的病原微生物,且不因浓度过高而产生过量的消毒副产物.实时水质模型对保持配水管网中余氯浓度处于最佳值具有重要作用,其准确性依赖于模型基于现场实测余氯数据的定期校准与验证.该研究应用遗传算法自动搜索氯衰减系数的最佳值,探究了管道分组对模型校准的影响,同时通过测试遗传算法处理数据不确定性的能力验证了其鲁棒性.
Abstract
Chlorine is the most common disinfectant to maintain the quality of drinking water in the water distribution networks.However,the concentration of chlorine is strictly restricted,which should be adequate to remove pathogens but not produce excessive disinfectant by-products.Hence real-time water quality model is very important for keeping the optimal target residual chlorine concentrations in the water distribution networks.The accuracy of water quality model can only be retained by regular calibration and validation utilizing field measured chlorine concentration data.In this research,a genetic algorithm is implemented to automatically search for the optimal value of chlorine decay parameters.An investigation of the impact of pipe grouping on the calibration performance is conducted.Further-more,the ability of genetic algorithm method in dealing with data uncertainties is tested to validate its robustness.
关键词
配水管网/余氯衰减/水质模型校准/遗传算法Key words
water distribution network/residual chlorine decay/water quality model calibration/genetic algorithm引用本文复制引用
出版年
2024
国家科技期刊平台
NSTL
万方数据