Conductivity Reconstruction of Brain Edema Based on Improved Adaptive Genetic Algorithm

In order to estimate the progression or regression of edema at the bedside continuously, based the theoretic model, an improved Adaptive Genetic Algorithm(AGA) has been applied in optimization of conductivity reconstruction. Dynamic crossover and mutation operators, which are based on Maiming Distance, are brought forward in this paper to maintain generation´s diversity. As a contrast, the Simple GA(SGA) has also been applied in same optimization of brain edema. It is shown the AGA not only has satisfied efficiency but also has enhanced the capability to converge to the best answer.