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.
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Felka, D., Brodny, J. (2018). Application of Neural-Fuzzy System in Prediction of Methane Hazard. In: Burduk, A., Mazurkiewicz, D. (eds) Intelligent Systems in Production Engineering and Maintenance – ISPEM 2017. ISPEM 2017. Advances in Intelligent Systems and Computing, vol 637. Springer, Cham. https://doi.org/10.1007/978-3-319-64465-3_15
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DOI: https://doi.org/10.1007/978-3-319-64465-3_15
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