Nature Inspired Bargain Optimization Algorithm for Effective Interpretation of Geoelectrical Data
Geoelectrical resistivity data collected from the ground contain lot of noises and errors. It requires efficient algorithm to reduce the errors to make an actual inversion models. Though different algorithm can be applied, nature inspired algorithm is more potential in inverting geoelectrical data in an elegant and comprehensive way. Bargain Optimization (BO) algorithm is framed on the concept of bargaining things to purchase for needs. In general, effective bargaining results in more profit and leads to loss when it fails. In this research work, Bargain Optimization algorithm is applied to invert geoelectrical data and the effective bargaining will take time to process and to obtain the required model. The input data is AB/2, apparent resistivity data and the inverted model through BO algorithm is successfully matched with the available litholog section of the study area. The output graphs have profit/loss bar graph, which reveals the status of bargaining during a particular number of epochs.