中国石油大学学报（社会科学版）Issue(3)：8-11,4.DOI:10.13216/j.cnki.upcjess.2015.03.0002
基于 BP 神经网络模型的中国石油需求预测研究
Research on Prediction of China's Oil Demand Based on the BP Neural Network Model
摘要
Abstract
The prediction of oil demand has great significance in preparing the oil industry development planning. In order to reasonably predict China's oil demand, take GDP, population, industrial structure and the technical progress as input vector and take the oil demand as the output vector, we establish the BP neural network model. After training of the BP neural network model by Matlab software, we find that when the number of hidden layer nodes for vector is 17, learning rate is 0. 1, training times are 8 and training precision is 0. 001, and the predicting result is the best. Finally, we use the BP neural network to predict China's oil demand from 2015 to 2024.关键词
BP 神经网络/石油需求/预测Key words
BP neural network/oil demand/prediction分类
管理科学引用本文复制引用
李宏勋,李元庆,王海军..基于 BP 神经网络模型的中国石油需求预测研究[J].中国石油大学学报（社会科学版）,2015,(3):8-11,4.基金项目
国家社会科学基金项目(12BJY075) （12BJY075）
中央高校基本科研业务费专项资金资助项目(13CX05044B) （13CX05044B）
