Estimation of Geodetic Velocity Field Based on Sigmoid Functions of Artificial Neural Networks

Based on 42 GPS velocity vectors existing in NW Iran، we estimated new velocity vectors for some arbitrary positions in study area by using two activation functions of Back Propagation Artificial Neural Networks (BPANN): “Sigmoid Function” and “Continuous Log-Sigmoid Function”. The results show sigmoid function’s RMSEs in E and N components are ±1 mm and ±1. 5 mm respectively which is less than Continuous Log-Sigmoid Function RMSE. So it seems BPANN method could be considered as a good alternative to estimate geodetic velocity field relative to other classical estimation methods.