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文章采用改进的混沌蚁群算法对新疆某冰川河流水质模型进行参数反演优化研究,并结合数值试验的方式对比改进前后算法对水质模型参数反演优化计算时效的影响。分析结果表明:改进后的算法在水质参数计算时效上有较为明显的提高,相比于传统算法,改进算法的粗搜索序列迭代次数平均减少90次,收敛率提高42.7%,计算时间均值减少0.499min。改进算法反演优化参数拟合的COD浓度数据和断面监测数据误差相比于传统算法减少15.9%,拟合系数提高0.24。研究成果对于新疆冰川河流水生态保护研究提供方法参考。
In this paper, an improved chaotic ant colony algorithm is used to optimize the parameters of a glacier river water quality model in Xinjiang. Combined with the numerical experiment, the influence of the improved algorithm before and after the optimization on the parameters of the water quality model is studied. The analysis results show that the improved algorithm has obvious improvement in the timeliness of water quality parameter calculation. Compared with the traditional algorithm, the improved algorithm reduces the number of iterations by 90 on average, the convergence rate increases by 42.7% and the calculated time decreases by 0.499 min. Compared with the traditional algorithm, the error of COD concentration data and cross-section monitoring data fitting by the improved algorithm of inversion optimization parameters is reduced by 15.9% and the fitting coefficient is increased by 0.24. The research results provide a reference to the research on the protection of glacier water in Xinjiang.