基于BP神经网络的邯郸岳城水库水质评价与预测研究

Evaluation and Prediction of Water Quality of Yuecheng Reservoir in Handan Based on BP Neural Network

BP神经网络具有非线性建模能力、适应性和泛化能力以及处理大量数据的能力,同时还具有可解释性和可视化的特点,能够实现实时监测和预测,使得BP神经网络成为水质评价与检测研究中重要的工具和方法。首先对BP神经网络基本原理和模型结构进行介绍,然后构建水质评价与预测的BP神经网络模型,并对岳城水库进行水质评价与预测,通过对BP神经网络的输出结果和水质分级标准相比较,可以看出两者之间较为吻合,可以用来进行水质的评价与预测。

BP neural network has the ability of nonlinear modeling,adaptability and generalization,and the ability to process large amounts of data.At the same time,it also has the characteristics of interpretability and visualization,which can realize real-time monitoring and prediction,making BP neural network an important tool and method in water quality evaluation and detection research.First,the basic principle and model structure of BP neural network are introduced,and then the BP neural network model of water quality evaluation and prediction is constructed,and the water quality evaluation and prediction of Yuecheng Reservoir is carried out.By comparing the output results of BP neural network with the water quality classification standard,it can be seen that the two are in good agreement,and can be used for water quality evaluation and prediction.