基于时间序列的神经网络水质参数预测方法的应用

Water Quality Parameter Prediction Using Neural Network Based on Time Series

为准确预测水质变化规律,利用一种基于时间序列的神经网络水质参数模型预测方法,将时间序列预测方法与神经网络非线性建模方法相结合,通过时间序列的历史数据揭示特定水环境中水质参数随时间变化的规律,再利用神经网络的强非线性和自适应学习能力来预测未来的水质参数变化趋势,并用南津关水质自动监测站的监测数据验证了该方法的有效性。

A prediction method using neural network based on time series is proposed to predict the change rule of water quality.Combining the time series prediction and non-linear neural network modeling method,the change rule of water quality parameter in the specific water environment is revealed based on the time-series historical data.The nonlinear neural network model with self-learning is used to predict the change trend of water quality parameter in the future time.The actual data of water quality monitoring station in Nanjinguan verify the effectiveness of the proposed method.