计算机与数字工程2019，Vol.47Issue(12)：2978-2981,3009,5.DOI:10. 3969/j. issn. 1672-9722. 2019. 12. 008
基于BP神经网络的深层感知器预测模型
Prediction Model of Deep Sensor Based on BP Neural Network
陈通 1周晓辉1
作者信息
- 1. 西安邮电大学计算机学院 西安 710061
- 折叠
摘要
Abstract
As is known to all,local financial revenue is an important part of the country. The scientific and rational prediction of local financial revenue can effectively overcome the randomness and blindness of the scale of budget. In the wave of big data. It is very important to be good at using data to predict and analyze financial revenue and transform a lot of trivial data into useful decision information. At present,most of the financial income combination forecasting models are all three layers of neural network structure. Aiming at the characteristics of fiscal revenue forecasting,combined with current fiscal revenue combination forecasting method and deep learning idea,a deep sensor prediction model based on BP neural network is proposed. It is a four layer neural network struc?ture,by using the data of Xi'an's fiscal revenue as the test sample,the model is proved to be of high precision,fast convergence and high accuracy with the promotion and practicality by comparing with the conventional BP neural network.关键词
数据挖掘/财政收入预测/深度学习/深层感知器Key words
data mining/fiscal revenue forecast/deep learning/DMLP分类
信息技术与安全科学引用本文复制引用
陈通,周晓辉..基于BP神经网络的深层感知器预测模型[J].计算机与数字工程,2019,47(12):2978-2981,3009,5.
