本文選題：PSO-DE + 污染物溯源��； 參考：《中國環(huán)境科學》2017年10期

【摘要】：利用PSO-DE混合優(yōu)化算法結(jié)合移動監(jiān)測平臺研究了污染物源項識別問題,包括單點固定源和多點固定源位置的反演.該方法把源項識別反問題轉(zhuǎn)化為非線性優(yōu)化問題,用N個移動平臺檢測并記錄所在水域的污染物濃度,將各自位置的坐標值記為此移動平臺的p_(best),每一個移動平臺均對應一個p_(best),即共有N個p_(best),將N個移動平臺獲取的污染物濃度值進行對比,選擇最大污染物濃度值對應的水域坐標,記為g_(best),以此作為初始種群先進行PSO優(yōu)化獲得的種群,再進行DE優(yōu)化,取兩者濃度高的作為g_(best),直到獲得濃度值最高的點,即污染物初始投放點.多個算例的計算結(jié)果表明,采用該算法對含點源的二維水域污染源溯源問題能夠得到精度較高的反演結(jié)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.
【作者單位】： 西安建筑科技大學信息與控制工程學院;
【基金】：住房和城鄉(xiāng)建設部科學項目計劃(2016-R2-045)
【分類號】：X52

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1 葛沈浩;基于PSO-DE的污水處理系統(tǒng)優(yōu)化控制與實現(xiàn)[D];浙江工業(yè)大學;2015年

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本文編號：1733263