Artificial neural networks have been used in many areas in geotechnical engineering applications. Adaptive neuro-fuzzy inference system (ANFIS) is used to predict vertical ultimate bearing capacity of single pile. The data of pile load test obtained from a literature are used to train ANFIS network and to determine the network parameters. The results show that the proposed modeling approach outperforms classical back-propagation (BP) neural network in terms of computational speed

forecast errors

efficiency. ANFIS is an effective method to achieve both high accuracy and less computational complexity for predicting vertical ultimate bearing capacity.