Comparios n of Application on Elman and BP Neural Networks in Discriminating Water Bursting Source of Coalmine
SUN Hao
Abstract：The discrimination of the mine water -bursting source is deemed to be a basic knowledge for the water control in the mines.A speedy and precise discrimination is of key importance to the safe production of the whole mine.This paper introduces SOFM neural networks and Back -propagation neural networks.Take Lijuzi Mine as an example , establishes the distinguishing model for water bursting by SOFM neural networks and BP neural networks with groundwater chemical characteristics , respectively.Experimental results show that the SOFM neural model is more precise and faster than BP neural model in discrimination.The SOFM neural model could better respond characteristics of groundwater systems.It provides an assistant means for decisiori -making to prevent water-inrush from coal floor.
Keywords：water bursting sourceelman neural networksback-propagation neural networksdiscrimi na-ting model
Publication Date：2014-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：5( 12-16 )