Abstract
The drive for efficient methods of testing design ideas and prototypes, particularly in engineering, has led to a rapid increase in the field of numerical simulation methods using computers, such as finite-element analysis. This increase in popularity has fueled the need for empirical models that interpolate data collected from these simulations. We propose a selection algorithm to efficiently explore an appropriate class of polynomial interpolators. The storage of polynomial models is made efficient and effective thanks to a special coding. Finally, the last stage of the algorithm returns a model that is no longer an interpolator but, having a smaller number of terms, is simpler and easier to handle and understand. In this way, a trade-off between accuracy and simplicity of the model is attained.