Risk assessment method of coal and gas outburst based on T-S fuzzy neural network
Yu Zhang, Wen Yang, Xinzhi Yu, Mingxuan Zhou, Chengpu Liu
Available Online March 2017.
- https://doi.org/10.2991/ifmca-16.2017.31How to use a DOI?
- T-S fuzzy neural network; Coal and gas outburst; Risk assessment
- Based on coal and gas outburst factors, combined with single gas risk index and comprehensive evaluation method to select evaluation index, in order to evaluate coal and gas outburst, evaluation of coal and gas outburst is established t-s fuzzy neural network model. Combined fuzzy logic and neural network, the model is realized in matlab software fuzzy neural network building, training, so as to realize the purpose of network evaluation. A Case Study of Pingdingshan No.13 Mine to evaluate the danger of coal and gas outburst, the final forecasting result is the same as actual results and different methods to predict the results of other researchers, suggests that feasibility and rationality of T-S fuzzy neural network model, offers a new way for gas outburst risk assessment..
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Yu Zhang AU - Wen Yang AU - Xinzhi Yu AU - Mingxuan Zhou AU - Chengpu Liu PY - 2017/03 DA - 2017/03 TI - Risk assessment method of coal and gas outburst based on T-S fuzzy neural network BT - Proceedings of the 2016 International Forum on Mechanical, Control and Automation (IFMCA 2016) PB - Atlantis Press SP - 193 EP - 197 SN - 2352-5401 UR - https://doi.org/10.2991/ifmca-16.2017.31 DO - https://doi.org/10.2991/ifmca-16.2017.31 ID - Zhang2017/03 ER -