A new predicting model based on fractional neural network combining global search ability of BP with fast local search ability of fractional order algorithm is presented to dynamically predict nonlinear gas emission quantity

aiming at present coal mine problems such as slow convergence speeding

easily trapped into local minima

etc.Both of training and the experimental results show that this model has better filtering effect

stronger anti-interference ability

faster convergence rate and higher prediction accuracy than the other models

which can meet requirements for exact guidance to practice.