Mojtaba Masoumi Shahr-babak - Ph. D. candidate, Department of Civil Engineering, Faculty of Engineering, Shahid Bahonar University of Kerman, Kerman, Iran
Mohammad Javad Khanjani - Prof., Department of Civil Engineering, Faculty of Engineering, Shahid Bahonar University of Kerman, Kerman, Iran
Kourosh Qaderi - Assistant Prof., Department of Water engineering, Faculty of Agriculture, Shahid Bahonar University of Kerman, Kerman, Iran

Suction caissons are major part of offshore structures and used in the anchorage system and foundation. Their stability must be satisfied. Main issue in suction caisson stability. Uplift capacity is the main issue in suction caisson stability. Several methods are proposed for uplift capacity prediction. Two of these methods are group method of data handling (GMDH) and arterial neural networks (ANN). In this study, the performance of GMDH and ANN in uplift capacity prediction is compered. For comparison using five statistical indices

Suction caisson, statistical indices, group method of data handling, arterial neural networks, and uplift capacity