Construction of legal incentive evaluation model based on BP neural network with multiple hidden layers
Jing Li · Journal of Physics Conference Series · 2021
Abstract BP neural network, the basic algorithm of deep learning, is a multilayer feedforward algorithm trained according to the error back propagation algorithm. BP neural network has the function of realizing any complex nonlinear mapping, which makes it especially suitable for solving problems with complex internal mechanism and has strong fitting ability. In this paper, the number, type, propagation rate and usage rate of the objects from 2013 to 2019 are collected as input and output neurons to establish a 6-layer BP neural network model. After experimental verification, the average relative error between the statistical value and the predicted value is 0.23%, which proves that the model has high prediction accuracy and can be applied in the evaluation of professional development.