Design of Water Quality Monitoring System in Yinma River Basin Based on Neural Network
Water Refined water quality monitoring can provide a scientific basis for water resources management.Artificial intelligence and deep learning technology have provided a new path for the intelligent monitoring of water quality.This study combines WebGIS and deep learning algorithms to design and implement a neural network-based water quality monitoring system.The system takes the water quality section data as the data support,trains the neural network model by dividing the data set,and fiinally realizes an integrated moni-toring system including GIS spatial operation module,basic data management module,water quality identification module,water quality chemical monitoring module and water body 3D visualization and other functions.Managers and users check the water quality status by visiting the system to realize remote real-time monitoring.After testing,the system can achieve the expected effect,which can meet the actual application needs,and is conducive to the protection of the ecological environment safety of the water area.
water quality monitoringneural networkYinma River basinGIS
NETL
NSTL
万方数据
