Water quality prediction method and device

Abstract

The invention provides a water quality prediction method, which comprises the following steps of building a water quality prediction model on the basis of a deep belief network and a long short time memory network; training a water quality prediction model on the basis of the historical water quality time sequence data and weather data; predicting the water quality on the basis of the water quality prediction model. The invention also provides a water quality prediction device, which comprises a building module, a training module and a prediction module. The water quality prediction method anddevice provided by the invention have the advantages that the deep belief network and the long short time memory network are introduced into the water quality prediction model; a great amount of water quality time sequence data and weather data are processed by using the deep belief network; the relationship between all factors is mined; the groundwork is laid for high-precision prediction difficult to realize the multi-variable nonlinear parameter data; on the basis of the deep belief network, the mass water quality time sequence data and weather data processing results are predicted on thebasis by studying the long-time relationship between the water body quality and the time sequence by the long short time memory network; the optimum prediction effect is obtained.

Description

technical field [0001] The invention relates to the field of water quality prediction, and more particularly, to a water quality prediction method and device. Background technique [0002] Economic development has made water pollution more and more serious, and the deterioration of national water quality has intensified. Water environment management has become an important measure to solve the shortage of water resources and the aggravation of water pollution. Water quality prediction and early warning are one of the important research contents of water environment problems. There are many factors that affect water quality, such as: air temperature, humidity, rainfall, solar radiation, wind speed, wind direction and other external environments, artificial pesticide application, aquatic organisms' own metabolism, excrement, microbial changes, etc., will affect the quality of water quality . The detection parameters of water quality parameters mainly include temperature, diss...

AI Technical Summary

Problems solved by technology

In this water quality prediction method, the key problem to be solved when RBF neural network is used in nonlinear system modeling is the selection of sample data. It is difficult to make accurate predictions for multivariable nonlinear water quality parameter data. More importantly, RBF neural network Unable to mine a large number of time series water quality parameter data characteristics

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