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本文(外文翻译-煤与瓦斯突出灰色-神经网络预测模型的建立.doc)为本站会员主动上传,图海文库仅提供信息存储空间,仅对用户上传内容的表现方式做保护处理,对上载内容本身不做任何修改或编辑。 若此文所含内容侵犯了您的版权或隐私,请立即通知图海文库(发送邮件至admin@thwenku.com或直接QQ联系客服),我们立即给予删除!

外文翻译-煤与瓦斯突出灰色-神经网络预测模型的建立.doc

1、翻译部分英文原文Establishment of grey-neural network forecasting model of coal and gas outburstYang Sheng-qianga, Sun Yana,b, Chen Zu-yuna, Yu Bao-haia, Xu QuanaaState Key Laboratory of Mine Resource and Safe Exploitation, School of Safety Engineering, CUMT, Xuzhou 221008, ChinabDepartment of Public Managem

2、ent, Shanghai Trade Union Polytechnic, Shanghai 201415, ChinaAbstract: Grey correlation analysis was made with respect to factors affecting coal and gas outburst and the input parameters of artificial neural network (ANN) determined. Then five dominant factors were chosen for grey correlation analys

3、is as the input parameters based on the improved BP algorithm, and neural network forecasting model of coal and gas outburst established. The network was trained by using the study samples from the instances of typical coal and gas outburst mines, and coal and gas outburst instances of Yunnan Enhong

4、 mine were used as forecasting samples. The comparison between the results from network forecasting with that of the traditional methods indicates that this method can meet the requirement for coal and gas outburst forecast .Keywords: coal and gas outburst ; grey correlation analysis; grey-neural ne

5、twork1. IntroductionIn china, coal has a wide distribution and the landforms of coal fields are complex. The coal production is threatened by water, fire, coal dust, roof fall, gas outburst, and so on. Of these factors, gas outburst is the most serious dangerous one to cause great economic loss and

6、kill coal miners. So, gas outburst forecasting becomes particularly important 1.Because the inherent mechanism of coal and gas outburst is so complicated and lots of uncertain and fuzzy problems exist between effect factors and accidents, both the traditional forecasting technologies based on experi

7、ence and the statistical forecasting technologies based on mathematical model are restricted in the field application. Grey-neural network forecasting methods of coal and gas outburst is applied in this paper.2. Analysis of effect factors 2.1. Initial velocity of gas ( p )The initial velocity of gas

8、 is one of the risk indexes for coal and gas outburst2-3. It shows the blow-off velocity of gas from coal. This index reflects how quickly the gas releases from coal seams. p is related to the gas content of coal, structure and surface property of pore. To a large degree, the movement and destructiv

9、e power of gas is decided by desorption and blow-off ability of gas in coal during the developing process of coal and gas outburst.2.2. Consistent coefficient of coal ( f )The consistent coefficient of coal is a kind of relative indexes of coal particles mechanical strength. Its value reflects coals

10、 physical and mechanical properties and is also an important parameter involved in coal and gas outburst. Generally, the bigger the f is, the more difficult the outburst happens under the same gas pressure and ground stress.2.3. Gas pressureGround stress controls gas pressure field and promotes coal

11、-body to be destructed by gas. The increased pressure in surrounding rock determines ventilation property of coal seams and leads to increase pressure gradient which is favorable for the coal and gas outburst to happen. The content of gas pressure is an important symbol of gas compressive energys va

12、lue.2.4. Thickness of soft sublayer The deeper the coal seam is, the more frequent the gas outburst happens. Both the outburst times and the scales increase with the increase of coal seam thickness, especially the thickness of the soft sublayer. Because the reason of low mechanical strength of coal

13、and bad ventilation property, much content and pressure of gas exists in the change area of coal bed thickness. 2.5. Coal-body destruction typeGround stresses, including self-weight stress, structural stress, and disturbance stress, get the surrounding rocks or coal-bodys elastic potential energy do

14、 work, making the coal-body destroyed and displaced. Coal-body destruction type refers to the coal-body destruction degree of coal-body structure under structural stress. According to the destruction degree, it can be divided into five types:1- non-destructive coal; 2-destructive coal; 3- strong des

15、tructive coal;4 - pulverized coal; 5-completely pulverized coal. 2.6. Mining depthViewing from the regional metamorphism of coal, the depth is the main reason lignite changing into anthracite because, with increase of depth, the pressure and temperature increases. The deeper the depth is, the higher

16、 the coal rank is. The huge thickness cover makes the gas be formed and protected, most of which are methane and so on. So the outburst intensity of coal will increase with the increase of mining depth.2.7 The Gas Content of Coal seamGas is from the coal seam, strata, gob or production process during mine excavation. The higher the gas content of coal seam is, the more gas will effuse into tunnels and working faces dur

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