Raman Spectroscopy System for Water Pollution Control based on Artificial Neural Network

Abstract

Water resources are an important material resource for living and production. China is a country with poor water resources, and at the same time, the existing water resources in China are all polluted to varying degrees, especially the quality of surface water is closely related to the quality of people's production and life. With the boom in artificial neural network (ANN) research, neural networks have now been used in a number of fields such as graphics processing, expert decision making systems, sound processing, etc. due to the advantages of ANNs themselves, which have achieved amazing results. The theory has turned into a new multifaceted avant-garde discipline associated with multiple fields. In recent years, ANN research has been gradually applied to environmental science, some of which have applied ANN research to areas such as water eutrophication prediction and water quality prediction. The application of ANN technology to surface water quality prediction is at an early stage, and its characteristics make it a great advantage in this field. This paper investigates the use of BP ANNs to predict surface water quality, to make rapid and accurate predictions of surface water pollution, and to provide decisions for the protection of water resources and pollution prevention.