Gas concentration prediction method and device based on extreme learning machine

An extreme learning machine and gas concentration technology, applied in special data processing applications, instruments, electrical digital data processing, etc., can solve problems such as unfavorable health of personnel, environmental air pollution, inability to complete gas information prediction and early warning functions, etc., to achieve The realization process is simple and efficient, and the effect of improving accuracy

Active Publication Date: 2014-10-29
DALIAN MARITIME UNIVERSITY
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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

Method used

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  • Gas concentration prediction method and device based on extreme learning machine
  • Gas concentration prediction method and device based on extreme learning machine
  • Gas concentration prediction method and device based on extreme learning machine

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Experimental program
Comparison scheme
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Embodiment Construction

[0049] like figure 1 A gas concentration prediction method based on an extreme learning machine is shown, including the following steps:

[0050] Step 1: Collect the concentration of each gas at a preset time interval, and perform step 2;

[0051] Step 2: Over time, for each gas, form M sequentially arranged historical gas concentration time series, each historical gas concentration time series contains a preset amount of gas concentration data, and the last historical gas concentration time series There is a preset time interval between the collection time point corresponding to the last gas concentration data and the current time point, and step 3 is performed;

[0052] Step 3: Over time, for each gas, construct a sample set that takes the h-1th historical gas concentration time series as input and the hth historical gas concentration time series as output, where 2≤h≤M; Multiple gases correspond to multiple sample sets, go to step 4;

[0053] Step 4: Divide each sample se...

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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...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F19/00
Inventor 刘丽波姜谙男郑子德王雪元
Owner DALIAN MARITIME UNIVERSITY
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