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Application of Neural-Fuzzy System in Prediction of Methane Hazard

  • Dariusz Felka
  • Jarosław Brodny
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 637)

Abstract

In the paper there are presented possibilities of use of artificial intelligence to build predictive models based on the measurement data. Fundamental problems concerning fuzzy logic, neural network and ANFIS system were discussed. This system connects capability of representation and processing of fuzzy logic and capability of learning of neutral networks. The ANFIS interface has been characterized relating to training a fuzzy model of Sugeno type. An example of using its interface to predicting of methane hazard in the region of mined longwall was presented. Predictive model based on the real methane measurement data from this longwall was developed.

Keywords

Neuro-fuzzy systems ANFIS interface Prediction of methane-bearing capacity in a mine 

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Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  1. 1.Institute of Innovative Technologies EMAGKatowicePoland
  2. 2.Silesian University of TechnologyGliwicePoland

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