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Gas concentration prediction method based on adaptive modularization neural network

A technology of gas concentration and neural network, which is applied in the field of gas concentration prediction based on adaptive modular neural network, can solve problems such as poor accuracy and extrapolation ability, weak robustness, and long learning time of prediction model

Inactive Publication Date: 2017-03-15
XIAN UNIV OF SCI & TECH
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Problems solved by technology

If the prediction model of a single neural network is used, it will often lead to defects such as too long learning time of the prediction model, poor accuracy and extrapolation ability. In addition, the single model also has the problem of forgetfulness, which makes its adaptive ability poor and its robustness not strong.

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  • Gas concentration prediction method based on adaptive modularization neural network
  • Gas concentration prediction method based on adaptive modularization neural network
  • Gas concentration prediction method based on adaptive modularization neural network

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Embodiment Construction

[0103] The specific implementation manners of the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. The following examples are used to illustrate the present invention, but are not intended to limit the scope of the present invention.

[0104] The gas concentration sensor is used to collect the gas data of the actual mining face of a coal mine, and use it as the prediction object to predict the gas concentration of the mine, such as figure 1 As shown, the specific method is as follows.

[0105] Step 1. Place the gas concentration wireless monitoring sensor in front of the coal wall, mining equipment and operators, and collect gas concentration data in different areas of the mine through the gas concentration sensor to truly reflect the gas at the front of the working face during the continuous movement of the excavator. The most real situation of the gushing amount, and set up a mobile base station 50-10...

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Abstract

The present invention provides a gas concentration prediction method based on an adaptive modularization neural network, and relates to the mine gas concentration detection technology field. The method comprises: collecting the gas concentration data, storing the gas concentration data in a gas concentration database, performing adaptive noise removing processing of the gas concentration data in the database to take the gas concentration data after the adaptive noise removing processing as chaotic time series, establishing the training sample set of an adaptive modularization neural network, constructing an adaptive modularization neural network soft measurement prediction model, and predicating the gas concentration by employing the constructed predication model according to the newly obtained gas concentration data and the historical data in the gas concentration database. The gas concentration prediction method based on the adaptive modularization neural network has a significant noise removing effect, can retain the useful information in the gas concentration time sequence while effectively removing the noise and can construct the soft measurement predication model of the adaptive modularization neural network, and the input information is integrally processed through a plurality of different submodels so as to improve the learning precision and the generalization performance of the predication model and improve the robustness of the prediction model.

Description

Technical field: [0001] The invention relates to the technical field of mine gas concentration detection, in particular to a gas concentration prediction method based on an adaptive modular neural network. Background technique: [0002] China is a country that uses coal as its main energy source. China's National Energy Medium and Long-Term Development Plan (2004-2020) clearly states that China will "adhere to coal as the main body, electricity as the center, and comprehensive development of oil, gas and new energy. Energy Strategy". The vast majority of my country's coal is mined underground, and underground production accounts for more than 95% of coal production, accounting for about 40% of the world's total coal mining. Due to the particularity of geological conditions in our country, all mines are gas mines, and more than half of the mines are in high gas areas or gas outburst areas. Coal mine gas disaster is one of the major disasters that threaten the safety of coal...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06N3/02G06N3/08G06Q10/04
CPCG06N3/02G06N3/08G06Q10/04
Inventor 张昭昭郭伟耿涛
Owner XIAN UNIV OF SCI & TECH
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