Gas concentration real-time prediction method based on dynamic neural network

Abstract

The invention provides a gas concentration real-time prediction method based on a dynamic neural network. Firstly, the neural network is trained by means of data in a mine gas concentration historical database, activeness of hidden nodes of the network and learning ability of each hidden node are dynamically judged in the network training process, splitting and deletion of the hidden nodes of the network are achieved, and a network preliminary prediction model is built; secondly, mine gas concentration information is continuously collected in real time and input into the prediction model of the neutral network to predict the change tendency of gas concentration in the future, and the network is trained timely through predicted real-time data according to the first-in first-out queue sequence to update a neutral network structure in real time, so that the neutral network structure can be adjusted according to real-time work conditions to improve gas concentration real-time prediction precision. According to the method, the neural network structure can be adjusted timely on line according to the real-time gas concentration data, so that gas concentration prediction precision is improved, and the technical requirements of a mine gas concentration information management system are met.

Description

technical field [0001] The invention belongs to the technical field of detection, aims at the requirement of real-time prediction of a mine gas concentration monitoring system, and in particular relates to a real-time prediction method of gas concentration based on a dynamic neural network. Background technique [0002] China is a country with large coal resources and a country with coal as the main energy source. The 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, oil and gas and Energy Strategy for the Comprehensive Development of New Energy". 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 ...

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Problems solved by technology

[0005] The purpose of the present invention is to overcome the defects that the neural network structure is difficult to determine and the prediction model is difficult to predict online in the current neural network gas concentration prediction model, and provides an online prediction model based on a dynamic neural network to realize real-time prediction of mine gas concentration

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