Water quality detection system and method based on gated recursive array

Abstract

The invention provides a water quality detection method based on a gated recursive array. The detection method comprises the following steps: S1, acquiring water quality parameter values including a PH value, conductivity, turbidity, dissolved oxygen, water temperature, content of chlorophyll A, content of blue-green algae, content of ammonia nitrogen, content of total phosphorus, content of copper, content of lead and content of tin; acquiring environmental indexes including atmospheric pressure, atmospheric humidity, atmospheric temperature and wind speed; S2, performing normalization and feature selection on the obtained water quality parameter values and environmental indexes to obtain preprocessed data; S3, selecting a neural network based on a gated recursive array as a prediction model, and setting a loss function and an optimization iteration method; S4, inputting the preprocessed data into a prediction model for model training to obtain a prediction result; and S5, comparing the prediction result with a set five-stage water quality classification to obtain a classification result. According to the method, the water quality attributes can be more effectively utilized for prediction and classification.

Description

technical field [0001] The invention relates to the technical field of water quality safety, in particular to a water quality detection system and method based on a gated recursive array. Background technique [0002] With the continuous development of my country's industrial and technological level, the industrial sewage, domestic sewage and other wastes caused by it enter lakes, reservoirs and other drinking water sources such as rivers, seas, lakes and seas, so that they exceed the self-purification capacity of water bodies and cause serious pollution. It will lead to changes in the physical, chemical, and biological characteristics of the water body, thereby affecting the use value of water, and even endangering human health and the ecological environment, causing gradual deterioration and eventually reaching an irreparable situation. Therefore, the development of real-time online, effective and rapid water quality monitoring system is of great significance for environmen...

AI Technical Summary

Problems solved by technology

However, these methods have some deficiencies, such as the lack of correlation in model building, and secondly, the model adopted does not have the time series function that can consider water quality data, which reduces the accuracy of water quality prediction work, and cannot obtain timely and effective results

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