Flower Pollination and Elitism Algorithms for Inversion of TDEM Data

Abstract

Hybridization of algorithms can enhance the overall search capabilities to get the optimal solution. The aim of this study was to invert Time Domain Electromagnetic (TDEM) data using the Flower Pollination Algorithm (FPA) as a new inversion scheme technique. FPA was originally inspired by the fertilization process of flowers, in which pollen transfer grains from male flowers to female flowers. The modeling of TDEM data was done by combining the FPA and elitism (eFPA) techniques. The applicability was tested on forward modeling data and observed data in MATLAB 2017a. In testing the algorithm, we used a model from homogeneous half space to a multi-layer model using different parameters (resistivity and thickness). In addition, in the inversion process, we used field data with various starting model approaches. Based on the results of the TDEM data modeling, FPA and eFPA can both be applied as algorithmic techniques for inversion modeling of TDEM data. The eFPA technique gave better results than FPA.