Geoid Determination Based on Log Sigmoid Function of Artificial Neural Networks: (A case Study: Iran)

A Back Propagation Artificial Neural Network (BPANN) is a well-known learning algorithmpredicated on a gradient descent method that minimizes the square error involving the networkoutput and the goal of output values. In this study, 261 GPS/Leveling and 8869 gravity intensityvalues of Iran were selected, then the geoid with three methods “ellipsoidal stokes integral”,“BPANN”, and “collocation” were evaluated. Finally obtained results were compared and bestthe method was introduced. In Iran, the consequences showed that “BPANN” has been superiorthan other methods. Root Mean Square Error of this algorithm was less than ±0.292 m.Therefore, we concluded that BPANN can be used for geoid determination as an excellentalternative to the classic methods.