Observatorio de I+D+i UPM

Memorias de investigación
Research Publications in journals:
Predicting the Risk of Fault-Induced Water Inrush Using the Adaptive Neuro-Fuzzy Inference System
Year:2017
Research Areas
  • Physics chemical and mathematical,
  • Non linear programming,
  • Linear programming,
  • Equations on partial differentials,
  • Computer aspects,
  • Numerical analysis on equations on partial differential,
  • Hydrogeology,
  • Engineering,
  • Mining production,
  • Mining operation
Information
Abstract
Sudden water inrush has been a deadly killer in underground engineering for decades. Currently, especially in developing countries, frequent water inrush accidents still kill a large number of miners every year. In this study, an approach for predicting the probability of fault-induced water inrush in underground engineering using the adaptive neuro-fuzzy inference system (ANFIS) was developed. Six parameters related to the aquifer, the water-resisting properties of the aquifuge and the mining-induced stresses were extracted as the major parameters to construct the ANFIS model. The constructed ANFIS was trained with twenty reported real fault-induced water inrush cases, and another five new cases were used to test the prediction performance of the trained ANFIS. The final results showed that the prediction results of the five cases were completely consistent with the actual situations. This indicates that the ANFIS is highly accurate in the prediction of fault-induced water inrush and suggests that quantitative assessment of fault-induced water inrush using the ANFIS is possible.
International
Si
JCR
Si
Title
Minerals
ISBN
2075-163X
Impact factor JCR
1,5
Impact info
Datos JCR del año 2015
Volume
7(4)
10.3390/min7040055
Journal number
55
From page
1
To page
15
Month
ABRIL
Ranking
MINERALOGY. 14/29 Q2 MINING AND MINERAL PROCESSING. 9/21 Q2
Participants
  • Autor: Qinglong Zhou (UPM)
  • Autor: Juan Herrera Herbert (UPM)
  • Autor: Arturo Hidalgo Lopez (UPM)
Research Group, Departaments and Institutes related
  • Creador: Grupo de Investigación: Recursos Minerales
  • Centro o Instituto I+D+i: Centro de Investigación en Simulación Computacional
S2i 2020 Observatorio de investigación @ UPM con la colaboración del Consejo Social UPM
Cofinanciación del MINECO en el marco del Programa INNCIDE 2011 (OTR-2011-0236)
Cofinanciación del MINECO en el marco del Programa INNPACTO (IPT-020000-2010-22)