Application of Fuzzy and RBF Neural Networks in the Prediction of Distribution of Coal Seams

Abstract

A prediction approach through fuzzy logic and RBF neural networks were proposed to determine the distribution of coal seam terrains. A triangular fuzzy set was selected as the fuzzification basis for this work. The triangular fuzzy sets was created for each factor involved in the experiment, and are divided according to the levels of factors used in the experiment. The fuzzy membership functions and rule bank were based on observations during cutting experiments using the shearer drum operations and the measurements from the electrical conductance sensor for sensing the variations in the electrical conductance value in the coal mines. Also an efficient output can be obtained by RBF neural network with trained set of data. Then data set training is being done and the mining process can be established