Modeling of material behavior data in a functional form suitable for neural network representation

Decision making through connectionist expert systems is getting adopted in various disciplines. For such systems the subject knowledge has to be represented by neural networks. A simple and fast method is developed for modeling of material behavior data in a functional form suitable for neural network representation. Complete algorithm for the method is given. The algorithm is used for modeling of material behavior data for several examples, taken from handbooks, etc. The error of approximation is very small in all the cases considered. The algorithm deals with cases where the property to be modeled is a function of one variable or its variation is measured with change of one parameter, keeping other parameters constant. The algorithm can also be used as a curve fitting technique, preserving the shape as desired by subject expert, even in presence of errors in the measurement data.