BP algorithm is widely used in calibrating measurement error of GPS height fitting.Conventional BP algorithm tends to get into infinitesimal locally

which worsens the stability of the measurement accuracy.An evolutionary neural network model based on IA-BP optimal algorithm is proposed.In the model

immene algorithm（IA）is first used for global search and then BP algorithm for local search.Experiment results indicate that the IA-BP optimal algorithm may effectively avoid getting into infinitesimal locally and have the merits of high prediction precision

rapid convergence

global superiority and accuracy for optimization.The results show that the root mean-square relative error is less than 0.042 2

the mean absolute relative error is less than 0.047 2

and the max absolute relative error is less than 0.050 3 between the predict value and the standard one.