River pollutant flux intelligent calculation and prediction method based on integrated neural network

Abstract

The invention discloses a river pollutant flux intelligent calculation and prediction method based on an integrated neural network. The method comprises the following steps: S1, inputting the historical data of pollutant concentration and river flow, discriminating the types of main pollutants of a river and the time-average change type of flow, and employing a support vector machine method of machine learning, intelligent classification of pollution source types and flow time-average change degrees of main pollutants of the river is realized; s2, according to the judgment of the main pollutants and the time-average change type in the S1, adjusting a pollutant flux calculation formula in combination with different requirements and objective conditions, and performing pollutant flux calculation; and S3, predicting the pollutant concentration and the river flow by applying a convolutional neural network method in combination with a long-short-term memory artificial neural network and a stack type auto-encoder, inputting predicted data of the pollutant concentration and the river flow into S1 for intelligent classification, and predicting the pollutant flux by applying S2 according to a classification result of S1 and in combination with the predicted data.

Description

technical field [0001] The invention relates to the technical field of river pollution, in particular to an intelligent calculation and prediction method for river pollutant flux based on an integrated neural network. Background technique [0002] In recent years, with the continuous advancement of my country's industrialization process, the problem of river pollution has also emerged. Taking the Pearl River Basin as an example, a large number of high-consumption and high-pollution industrial parks have been established. The industrial planning of these parks and surrounding areas is not perfect, and the sewage treatment is not good. If it is in place, it will have an adverse impact on the water quality of the Pearl River. An extremely important step in controlling river pollution is to calculate and predict the pollution flux of each river, quantify the severity of each river's pollution, clarify the main pollutants of each river, and use these data to guide the government o...

AI Technical Summary

Problems solved by technology

However, due to the significant spatio-temporal changes in the types of pollution sources (point source / area source), the impact of the runoff change rate of each river on the pollutant flux amplitude is also significantly different. If the flux calculations for different rivers and different pollutants use The same calculation algorithm will lead to deviations between the calculation results and the actual situation

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