Efficient design of electromagnetic field exposure maps with multi-method evolutionary ensembles

Radio-frequency electromagnetic field (EMF) exposure is a growing concern among the population. This concern has led to a need for practical tools to contribute to an adequate risk perception. Representing spatial variations af-ter measurements from fixed sites and interpolating using different techniques is the most suitable method for obtaining EMF high-quality exposure maps. This paper uses evolutionary computation to obtain the optimal set of points to construct high-quality electromagnetic field exposure maps (minimizing an error measure with respect to a reference exposure map). A multi-method en-semble evolutionary approach, able to combine different search operators in a single population (PCRO-SL), is introduced for this particular problem, and it has been tested over actual measurements at Meco town, Madrid, Spain, obtaining good quality electromagnetic field exposure map reconstructions in terms of the differences with a reference EMF exposure map. The results obtained show that reducing the number of measurement points necessary to obtain significant exposure maps, while maintaining their representativeness, is possible.