In traditional BP algorithm

the number of hidden layer neurons is uneasy to select.Aiming at sorting out this problem

this article points out the updated BP arithmetic model

which is DBP(Double BP) network model.The new model can adjust hidden layer neurons dynamically and automatically

which means

adjust the hidden layer neurons in another BP network dynamically via a experience and knowledge BP network

make the training error curve decrease rapidly by choosing the proper weight and thresholds.It sorts out the problem in the quantity of hidden layer neurons in BP network topology

as well as the issue of choosing the new added weight and threshold.In addition

it suggests a new approach against how the BP network escapes from the fake saturated area.Finally

it gets a good result through simulation.