Applications of Artificial Neural Network in Slag Glass-Ceramic Expert System
矿渣微晶玻璃材料设计神经网络模型

Artificial neural network was introduced into slag glass-ceramic material designing. A 3 layers feedforward network was built with a new robust learning algorithm, based on a concept of " entire error modifying ". The network has a excellent learning ability when its topology is M-2M-1 and an appropriate study error chosen. The research results show that this slag glass-ceramic neural network is robust, quick and stable in training and data predicting, which can disclose the relationship of elemental compositions, structure and material properties of slag glass-ceramic effectively, even if some parameters are absent in samples.