IGOA-RBF模型在石门水库水质预测中的应用OA
Application of IGOA-RBF model in water quality prediction of Shimen Reservoir
文中以石门水库为例,通过改进蚱蜢算法(IGOA)增加局部值的泛化性,并对RBF神经网络模型进行参数优化,构建了运行效率高、预测精确度高的IGOA-RBF的水质预测模型.结果表明,IGOA-RBF水质预测模型误差均较小,可为水源地水环境的水质评价和治理提供重要参考.
This paper takes Shimen Reservoir as an example,by improving the Grasshopper Algorithm(IGOA)to increase the generalization of local values,and optimizing the parameters of the RBF neural network model,the IGOA-RBF water quality prediction model with high efficiency and high prediction accuracy is constructed.The results show that the error of IGOA-RBF water quality prediction model is small,which can provide important reference for water quality evaluation and treatment of water environment in water source.
孙晓蕾
辽宁省营口水文局,辽宁营口 115003
环境科学
IGOA-RBF连续流动分析法总磷总氮水质预测模型石门水库
IGOA-RBFcontinuous flow analysis methodtotal phosphorustotal nitrogenwater quality prediction modelShimen Reservoir
《东北水利水电》 2024 (006)
26-27,41 / 3
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