Prediction of the Coal and Gas Outburst by Neural Network

You, Wei; Wang, Kun; Li, Huixiao; Jia, Yang; Wu, Xiaoqin; Du, Yaning

doi:10.1109/iscid.2009.247

Search citation statements

Order By: Relevance

Paper Sections

Select...

Introduction1

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2015

Publication Types

Select...

Article1

Relationship

Self Cite0

Independent1

Authors

Journals

Cited by 1 publication

(1 citation statement)

References 7 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Coal and gas outbursts also do not always show direct quantitative relationships with these factors, so that forecasting them can be difficult. In existing studies, a variety of methods have been used to evaluate coal and gas outbursts, such as fuzzy synthetic evaluation, neural network evaluation, and extension clustering [1][2][3], to determine measures to reduce the loss induced by sudden occurrences [4].…”

Section: Introductionmentioning

confidence: 99%

Application of gray target models in the prediction of coal and gas outburst: the case of jinzhushan coal mine in China

Hu¹,

Peng²,

Xu³

et al. 2015

Int. J. SAFE

View full text Add to dashboard Cite

Coal and gas outbursts in coal mines are a complex dynamic geological phenomenon. A gray target model has been established based on the gray system theory to predict coal and gas outbursts. The model considers four influencing factors for coal and gas outbursts: gas pressure, destructive type of coal, coal rigidity, and initial speed of methane diffusion. Each weight of the factors is given through an improved analytic hierarchy process without consistency checks, and the accuracy of the assessment is high. By using the model, coal and gas outbursts in the Jinzhushan mine were predicted. Results demonstrate the viability of the gray target model in the prediction of coal and gas outbursts.

show abstract

Section: Introductionmentioning

confidence: 99%