基于PSO-DE算法的突发水域污染溯源研究

发布时间：2018-04-10 22:46

本文选题：PSO-DE + 污染物溯源　；参考：《中国环境科学》2017年10期

【摘要】：利用PSO-DE混合优化算法结合移动监测平台研究了污染物源项识别问题,包括单点固定源和多点固定源位置的反演.该方法把源项识别反问题转化为非线性优化问题,用N个移动平台检测并记录所在水域的污染物浓度,将各自位置的坐标值记为此移动平台的p_(best),每一个移动平台均对应一个p_(best),即共有N个p_(best),将N个移动平台获取的污染物浓度值进行对比,选择最大污染物浓度值对应的水域坐标,记为g_(best),以此作为初始种群先进行PSO优化获得的种群,再进行DE优化,取两者浓度高的作为g_(best),直到获得浓度值最高的点,即污染物初始投放点.多个算例的计算结果表明,采用该算法对含点源的二维水域污染源溯源问题能够得到精度较高的反演结果.
[Abstract]:The problem of pollutant source term identification is studied by using PSO-DE hybrid optimization algorithm and mobile monitoring platform, including the inversion of the location of single point fixed source and multi point fixed source.In this method, the inverse problem of source term identification is transformed into a nonlinear optimization problem, and N mobile platforms are used to detect and record the concentration of pollutants in the water area.As the initial population, PSO optimization is carried out first, then DE optimization is carried out, and the high concentration of both is taken as the best one until the highest concentration point is obtained, that is, the initial pollutant release point.The calculation results of several examples show that the proposed algorithm can obtain the accurate inversion results for the two-dimension water source tracing problem with point sources.
【作者单位】：西安建筑科技大学信息与控制工程学院;
【基金】：住房和城乡建设部科学项目计划(2016-R2-045)
【分类号】：X52

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