Forecasting the Production of Fully-Mechanised Coal Face by Meta-Synthetic AI Method

Being analysed systematically, the factors influencing the production of fully-mechanised coal face have been divided into geological, mining technical, and management groups. Artificial neural network-expert systems (ANN-ES) are established to decide the influencing factorsÆ membership grade; genetic algorithm-artificial neural network (GA-ANN) are used to decide the weights; fuzzy comprehensive evaluation method is used to calculate the integration indexes. Finally, the GA-ANN model is established to forecast the production of fullymechanised coal face. It is proved that the model is reliable with higher precision. The production of fully-mechanised coal face is influenced by many factors. However, some influencing factors are neglected by the traditional forecasting methods, the results of which are not precise and hardly be used as a guide for mine production and management. The relation between the production of fully-mechanised coal face and its effecting factors is analysed, and the meta-synthetic AI approaches are used to forecast the production of fully-mechanised coal face.