The goal of this work is to develop an accurate, efficient and robust algorithm for minimum zone circle roundness. In this paper, we use an interval bias adaptive linear neural network (NN) structure together with a least mean squares (LMS) learning algorithm, and an appropriate cost function to carry out the interval regression analysis. Through the system transformation, the minimum zone roundness can be related to a linear programming (LP) problem, which can be solved by the interval regression method. The interval regression method by NNs developed in this paper is applicable in linear regression analysis which has a complicated constraint, and where the least squares (LSQ) method cannot be used.
