What is it about?
According to the "national surface water monitoring and evaluation scheme for the 14th Five-Year plan" issued by the Ministry of ecological environment of the people's Republic of China, this study constructs a back propagation (BP) neural network model for comprehensive water quality evaluation with five indexes of pH value, dissolved oxygen, ammonia nitrogen, permanganate index and total phosphorus as input characteristic parameters. Some historical monitoring data in 2021 provided by Nanchong surface water monitoring station are randomly selected for water quality classification test. The experimental results show that the comprehensive evaluation method of water quality based on BP neural network proposed in this study is more reasonable than the classification result of water quality grade obtained by single factor evaluation method.
Featured Image
Photo by Christopher Gower on Unsplash
Why is it important?
The comprehensive evaluation method of water quality based on BP neural network proposed in this study is more reasonable than the classification result of water quality grade obtained by single factor evaluation method.
Perspectives
写这篇文章是一件非常愉快的事情，因为它有与我有长期合作的共同作者。并最终更多地参与水质检测研究
chen yang
China West Normal University
Read the Original
This page is a summary of: ∗Application of BP Neural Network Model in Surface Water Quality Evaluation, December 2022, ACM (Association for Computing Machinery),
DOI: 10.1145/3579895.3579932.
You can read the full text:
Contributors
The following have contributed to this page
