Gas concentration prediction method and device based on extreme learning machine

Abstract

The invention discloses a gas concentration prediction method and device based on an extreme learning machine. The method comprises the steps that over time, historical gas concentration time sequences arranged sequentially are formed for each kind of gas; a sample set with the h-1 historical gas concentration time sequence as input and with the h historical gas concentration time sequence as output is built for each kind of gas; each sample set is divided into a training sample set and a test sample set; by means of the optimal input layer weight and hidden layer offset, training and learning are carried out on each training sample set through the extreme learning machine, and concentration prediction evolution extreme learning models corresponding to different kinds of gas respectively are obtained; the last historical gas concentration time sequence of each kind of gas is adopted as input, a future gas concentration time sequence of each kind of gas is output according to the corresponding concentration prediction evolution extreme learning model. According to the gas concentration prediction method and device based on the extreme learning machine, the implementation process is simple and efficient, and prediction accuracy is improved.

Description

technical field [0001] The invention relates to a gas concentration prediction method and a system thereof, in particular to a gas concentration prediction method and a device thereof based on an extreme learning machine. Background technique [0002] Chemical laboratories involve a variety of chemicals, and related gas products will be produced when personnel conduct experiments, which may include CO 2 , CO or H 2 S and other gases harmful to human health. Since the content of harmful gases changes rapidly during the test, personnel are always operating indoors at this time. If the concentration of these gases exceeds a certain limit, it will cause great harm to human health. As people pay more and more attention to health, the monitoring and early warning of laboratory gas is very important. Harmful gas monitoring and alarm devices in the prior art can usually only monitor harmful gas in real time, and cannot complete the prediction and early warning functions of gas in...

AI Technical Summary

Problems solved by technology

Harmful gas monitoring and alarm devices in the prior art can usually only monitor harmful gas in real time, and cannot complete gas information prediction and early warning functions. When harmful gas is detected, it is very likely that the harmful gas has caused environmental air Pollution, harmful to human health

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