瓦斯突出

煤与瓦斯突出预测综合指标F值的试验研究

Test and research on comprehensive index F value for prediction of coal and gas outburst

基于贝叶斯正则化BP人工神经网络的煤与瓦斯突出预测的研究

Research of Prediction of Coal and Gas Outburst Based on BP Artificial Neural Network Utilizing Bayesian Regularization

运用扫描电子显微镜（SEM）对瓦斯突出煤进行了显微结构研究。

The microstructure of gas-outburst coal was studied by using Scan Electric Microscope ( SEM ) .

对GIS技术、无线电波透视探测技术及以地震波为主的弹性波技术为煤与瓦斯突出预测技术的发展前景作了必要的分析。

Necessary analysis of the future development is also provided for coal and gas outburst prediction by Geographical Information System ( GIS ), radio wave nondestructive detection and elastic wave technique based mainly on seismic waves .

本文用自适应模糊神经网络技术建立煤与瓦斯突出预测系统，以模糊数学作为表达与处理不精确数据、模糊信息条件的手段，以自适应BP神经网络作为解决问题的途径。

The authors set up the forecasting system with fuzzy-neural network theory , by means of fuzzy mathematics to express and deal with the imprecise data and fuzzy information , and utilized self-adaptive neural networks system to solve the problems .

针对原有Hopfield网学习算法的局限性，利用Hopfield网的非线性逼近能力来模拟煤与瓦斯突出中各指标的复杂非线性关系，通过联想记忆功能对煤与瓦斯突出进行分类。

In order to overcome the weakness of Hopfield learning , using the nonlinear approaching ability of Hopfield , nonlinear relations of indexes in coal and gas outburst are simulated and the species of coal and gas outburst are classified by association - memory .

基于各种原理的监测方法很多，利用声发射（AE）信号参数预测预报煤与瓦斯突出危险性，被许多国家的研究人员公认为是一种最有发展前途的方法。

There are many monitoring methods based different kinds of theory , the utilization of AE signal parameter to predict and forecast coal and gas outburst hazard is a method that is universally accepted by researchers in many countries and has the most developmental prospect .

本文采用分子模拟的巨正则系综蒙特卡洛方法（GCMC）和分子动力学方法（MD），通过比较甲烷在构造煤和相应的原生结构煤中吸附及扩散的差异，旨在寻求瓦斯突出的微观原因。

The objective of this work is to explore microscopic reasons to gas outburst by comparing the differences of adsorption and diffusion for methane in deformed coal and corresponding undeformed coal using molecular simulation of grand canonical Monte Carlo ( GCMC ) and molecular dynamic ( MD ) simulation .

瓦斯突出煤体探测的物性前提及应用

Physical property of gas outburst coal and its application in detection

我国预防煤和瓦斯突出的主要措施

On Main Measures to Prevent Coal and Gas Outburst in China

关键层-应力墙瓦斯突出机理

Key Layer and Stress Dike Mechanism of Coal and Gas Outbursts

煤田地质构造与瓦斯突出关系分形研究

Fractal research of relation between geological tectonic coalfields and gas outburst

在构造复合部位易于发生瓦斯突出。

Outburst is likely to occur in the structural composite parts .

《采区煤与瓦斯突出预测图》编图规则探讨

Discussion about Mapping Rules of Coal & Gas Outburst Prediction Plan

地质指标在煤与瓦斯突出预测中的应用研究

Applications Research of Geological Indexes in Coal and Gas Outburst Prediction

地质构造控制煤和瓦斯突出作用类型研究

Research on the types of geological tectonic controlling coal gas outbursts

煤与瓦斯突出煤层重烃组分的研究

Study on composition of hydrocarbons in coal seams liable to outbursts

煤与瓦斯突出危险区域划分研究

Study on Danger Zone Compartment of Coal and Gas Outburst

高瓦斯突出矿井巷道布置与施工

Roadway layout and construction in mine with potential gas outburst

隧洞施工中防治煤与瓦斯突出

Prevention and Control of Outburst of Coal and Gas During Tunnel Construction

煤与瓦斯突出电磁辐射的监测及应用

Monitoring and Application of Electromagnetic Emission Produced by Coal and Gas Outbursts

防治煤与瓦斯突出技术研究与探讨

Research on the technology of preventing coal and gas outburst

煤和瓦斯突出与太阳黑子活动的关系

Relation between Coal and Gas Outbursts and Activities of Sunspot

中高压注水瓦斯突出的综合防治

Comprehensive Control of Gas Outburst by Means of Medium High

煤与瓦斯突出区域预测信息系统开发

Development of coal and gas outburst regional prediction information system

褶曲分形特征及其与瓦斯突出关系研究

The research on folds fractal features and its relationship to gas outbursts

研究了度量煤与瓦斯突出这个复杂系统的相对标度不变量分维数。

The comparatively invariant fractal dimension is measured coal and gas outburst .

煤与瓦斯突出冲击波传播规律的实验研究

Experimental Study on Shock Wave Propagation Law of Coal and Gas Outburst

基于信息融合预测瓦斯突出方法的研究

Research on prediction of gas outburst based on information fusion

高瓦斯突出煤层快速揭煤方法研究

Study on the Quick Cutting Method of High Gas Outburst Coal Seam