Gas outburst predicting method based on EMD and ELM

A technology of gas outburst and prediction method, which is applied in the field of coal mine safety production, can solve problems such as falling into local minimum points and slow training speed, and achieve good adaptability and high prediction accuracy

Inactive Publication Date: 2015-04-22
ANHUI UNIV OF SCI & TECH
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Problems solved by technology

Among them, there are many researches on the gas outburst prediction model based on the neural network, but the traditiona

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  • Gas outburst predicting method based on EMD and ELM
  • Gas outburst predicting method based on EMD and ELM
  • Gas outburst predicting method based on EMD and ELM

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Embodiment Construction

[0036] The technical solutions of the present invention will be described in detail below in conjunction with the accompanying drawings.

[0037] Such as figure 1 As shown, the present invention provides a kind of gas outburst prediction method based on EMD-ELM, comprises the following steps:

[0038] (1) Acquire gas concentration time series through known data;

[0039] (2) Using empirical mode decomposition (EMD) to decompose the time series of gas concentration into intrinsic mode components and residual components;

[0040] (3) Carry out network training to extreme learning machine ELM;

[0041] (4) Utilize the trained ELM network to carry out modeling prediction to the EMD decomposition result of step (2);

[0042] (5) Reconstruct the prediction result of step (4) to obtain the gas concentration prediction value.

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Abstract

The invention discloses a gas outburst predicting method based on EMD (Empirical Mode Decomposition) and an ELM (Extreme Learning Machine). Firstly, the EDM is utilized for decomposing a gas concentration time sequence into a series of subsequences and residual volumes to reduce the computing scale of the local analyzing of gas concentration signals and improve the predicting accuracy; secondly, the ELM prediction is carried out on the subsequences and residual volumes; finally, the prediction values of the subsequences and the residual volumes are combined to obtain a final prediction value. According to the predicting method, the coal and gas outburst can be accurately predicted, convenience is provided for taking effective prevention measures in a targeted mode, and the prevention capacity of the gas accident is improved.

Description

technical field [0001] The invention relates to the field of coal mine safety production (prediction), specifically a gas outburst prediction method combining Empirical Mode Decomposition (EMD) and extreme learning machine (Extreme Learning Machine, ELM). Background technique [0002] As a primary energy source, coal is an important pillar of my country's national economic development. In my country, coal mines are mostly gas-containing mines, of which high-gas mines account for about 35%. Coal and gas outbursts are the primary problem that threatens the safety of coal mine production. Therefore, it is necessary to accurately predict coal and gas outburst in order to take effective preventive measures and improve the ability to prevent gas accidents. [0003] At present, there are mainly two types of methods for gas outburst prediction research: (1) gas outburst prediction based on the quantitative relationship between various relevant factors (geological and mining factors...

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Application Information

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IPC IPC(8): G06Q10/04G06Q50/02
CPCG06Q10/04G06Q50/02
Inventor 辛元芳姜媛媛
Owner ANHUI UNIV OF SCI & TECH
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