IA-BP optimal algorithm in measuring tobacco moisture content with resonant microwave sensor

BP algorithm has been widely used in calibrating measurement results detected by microwave resonator for improvement of accuracy. 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 this paper. In the model, IA algorithm is first used for global search and then BP algorithm for local search. Experiments indicated that the IA-BP optimal algorithm effectively avoid getting into infinitesimal locally and has the merits of high prediction precision, rapid convergence, global superiority and accuracy for optimization, which improves the measurement accuracy with the mean squared error 0.0125, the mean absolute error 0.0715, the mean relative error 0.1186 and the certain coefficient 0.9965 between the predicted moisture content and the real value.