粒子群算法在湖泊富营养化综合评价中的应用  

Application of particle swarm optimization algorithm to assessment of lake eutrophication

作　　者：欧阳峰[1] 周扬[1] 芦垒[1] 骆珍珍[1] 

机构地区：[1]西南交通大学环境科学与工程学院,四川成都610031

出　　处：《广东农业科学》2009年第2期85-87,93,共4页Guangdong Agricultural Sciences

摘　　要：适当设定湖泊富营养化指标"参照"值,将修正的卡森指数公式中的指标值用相对于"参照"值的指标"相对值"替换,公式中的参数可视为与指标特性无关。对公式中的待定参数采用粒子群算法进行优化,得到对多项指标都通用的营养状态普适指数公式,将优化后的营养状态普适指数公式用于我国不同地域和不同类型的20个湖泊的实例评价,并与其他评价方法进行比较,结果表明该模型具有实用性和可行性。Based on the hypotheis of ＂base values＂ of eutrophication indexes, an universal Cadson＇s index formula, in which parameters are independent on the characters of indexes, was presented for the eutrophic state of lakes, as the relative values of indexes were used instead of their monitoring values. Optimization of parameters in formula was carried out using particle swarm algorithm to derive an universal of evaluation of lake eutrophication suited to multi-index. And this formula was used to assess twenty lakes of different area and types. Comparing with the assessment results by other method, the results of optimized model indicate the practicability and feasibility.

关 键 词：湖泊 富营养化 粒子群算法 普适指数公式 参数优化 

分 类 号：X824[环境科学与工程—环境工程]