Predicting the risk of fault-induced water inrush using the adaptive neuro-fuzzy inference system

Zhou, Qinglong and Herrera Herbert, Juan and Hidalgo Lopez, Arturo (2017). Predicting the risk of fault-induced water inrush using the adaptive neuro-fuzzy inference system. "Minerals", v. 7(4) (n. 55); pp. 1-15. ISSN 2075-163X. https://doi.org/10.3390/min7040055.

Description

Title: Predicting the risk of fault-induced water inrush using the adaptive neuro-fuzzy inference system
Author/s:
  • Zhou, Qinglong
  • Herrera Herbert, Juan
  • Hidalgo Lopez, Arturo
Item Type: Article
Título de Revista/Publicación: Minerals
Date: April 2017
ISSN: 2075-163X
Volume: 7(4)
Subjects:
Faculty: E.T.S.I. de Minas y Energía (UPM)
Department: Ingeniería Geológica y Minera
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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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.

More information

Item ID: 50169
DC Identifier: http://oa.upm.es/50169/
OAI Identifier: oai:oa.upm.es:50169
DOI: 10.3390/min7040055
Official URL: http://www.mdpi.com/2075-163X/7/4/55
Deposited by: Memoria Investigacion
Deposited on: 13 Apr 2018 06:56
Last Modified: 30 May 2019 08:22
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