Gas outburst prediction based on the intelligent D-S evidence theory
by Caixia Gao; Fuzhong Wang; Zhan Zhang
International Journal of Computer Applications in Technology (IJCAT), Vol. 59, No. 2, 2019

Abstract: In this paper, the predicted model of gas outburst is built by combining fuzzy neural network and D-S evidence theory, the overall structure design of gas outburst predicted model is presented, the selection of gas outburst evaluation indicators, the design of fuzzy neural network unit and the design of D-S evidence theory unit are introduced. The eight key factors are selected as the evaluation indicators of gas outburst, and the preliminary judgment of gas outburst state in local point, is made by fuzzy neural network, and then global judgment of gas outburst state in mining working face is made based on D-S evidence theory. The simulated result shows that this method can make accurate judgments of gas outburst state grade, and regarding the judgments of the three kinds of gas outburst state, the accuracy error is less than 0.0048% and the uncertainty value approximates to 0.

Online publication date: Fri, 22-Feb-2019

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Computer Applications in Technology (IJCAT):
Login with your Inderscience username and password:

    Username:        Password:         

Forgotten your password?


Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com