Environment parameter real-time prediction method, terminal equipment and storage medium

Abstract

The invention relates to an environmental parameter real-time prediction method, terminal equipment and a storage medium, and the method comprises the steps: S1, receiving environmental data at a moment t, carrying out the normalization processing, and initializing a set variable a = 1 and the number of prediction times A; s2, inputting the normalized environmental data at the moment t into an environmental data prediction model, and outputting the model as an output result at the moment t + a * T; s3, performing reverse normalization processing on the output result at the t + a * T moment toobtain environmental data at the t + a * T moment; s4, inputting the output result of the t + a * T moment into an environmental data prediction model, and taking the output of the model as the outputresult of the t + (a + 1) * T moment; s5, performing reverse normalization processing on the output result at the t + (a + 1) * T moment to obtain environmental data at the t + (a + 1) * T moment; s6, judging whether a < A is true or not, if yes, setting a = a + 1, and returning to S4, otherwise, ending. The method predicts the environmental data at the moment when the environmental data cannot be monitored in real time through a machine learning algorithm and the actually monitored environmental data, and achieves the purpose of monitoring the environmental data in real time.

Description

technical field [0001] The invention relates to the field of environment detection, in particular to a method for real-time prediction of an environment parameter, a terminal device and a storage medium. Background technique [0002] With the advancement of industry and transportation in modern society, social productivity has developed unprecedentedly, and the emissions of industrial smoke and vehicle exhaust have seriously surpassed the purification ability of nature, causing irreversible impacts on the environment, followed by air pollution problems It has become more and more serious and has brought great harm to people's health. In particular, air pollution such as PM2.5, sulfur dioxide, nitrogen dioxide, and indoor formaldehyde and benzene series have a greater impact on human health. Among them, PM2.5, also known as fine particulate matter, fine particles, and fine particles, refers to particulate matter in the ambient air with an aerodynamic equivalent diameter less...

AI Technical Summary

Problems solved by technology

However, most of the existing air quality detection equipment on the market, although integrating many sensors, can detect harmful substances in the air, but the detection cycle is long and cannot be monitored in real time

Images