基于RBF神经网络的水质多因素预测

水质模拟预测是顺利实现水环境规划管理、水污染综合防治等任务不可缺少的基础工作。机理性水质模型虽考虑了影响水质变化的诸多因素,模拟预测效果较理想,但往往较复杂并需要大量基础资料与数据,使其进一步应用受到限制。基于RBF神经网络理论及其算法建立水质中四种污染物浓度的预测模型,应用结果表明,该方法可行,可以为水质污染预测提供一种有效的新手段。

Water Quality Prediction Based on RBF Neural Network

Water quality prediction is the indispensably basal work during favorable accomplishment on planning and managing of water environment and integrated controlling of water pollution.A good many factors which influence water quality are considered in mechanic models of water quality prediction,and simulation or prediction effects are satisfying.But sometimes mechanic models are complex and mass data is required,and farther application of mechanic models is limited.With application of RBF neural network theory...