Interpretation of gravity anomalies of Idealised bodies using global Particle swarm optimization technique

Amplitude coefficient factor (ACF), Shape factor (SF) and depth are standard qualitative parameter for interpreting various geometrical bodies. There are several optimization methods are available to invert the gravity anomaly caused by various geometrical bodies. But still the interpretation of gravity anomalies needs more accurate and realistic model parameter for better interpretation. To overcome the above problem, global Particle swarm optimization (PSO) is validated to synthetic gravity anomalies over various geometrical bodies and finally applied to field gravity data of various terrains to find the gravity parameters ACF, SF and depth of the geometrical bodies. Number of exercises has made to optimize the parameters such as ACF, SF and depth using various iterations. The optimized parameters have been compared with published results obtained by different methods that show a significantly good agreement with real model parameter. Thus PSO is an efficient and more robust technique to achieve optimal solution with minimal error.