The computational intelligences such as artificial neural network (ANN) and fuzzy inference system (FIS) along with Statistical Methods are strong tools for prediction, classification and optimization in engineering applications. In this paper, radial basis function (RBF) network, Multi-layer Perceptron (MLP) and Response Surface Methodology (RSM) are used and compared for prediction of bending length of wool fabric. For developing of the proposed models, the input parameters are SHP (%), BTCA (%) and Nano ZnO (%) and the output is bending length (cm). Results show that there are no significant differences among the methods.
