安徽农业科学2012，Vol.40Issue(9)：5712-5714,3.
基于GM(1,1)-BP神经网络的城市耕地数量预测研究
Study on the Forecasting Method for Urban Cultivated Land Quantity Based on GM (1, 1 )-BP Neural Network
王兵 1胡月明 1雷霆 1赵小娟1
作者信息
- 1. 华南农业大学信息学院,广东广州510642
- 折叠
摘要
Abstract
Based on the grey theory and BP neural network, we build up the composition model of GM (1,1) -BP neural network. From combining the advantages of temporality and disorder of grey model with the characteristics of self-learning and self-organization of BP neural network , we can forecast the farmland quantity with the combining model. The results show that compared with the grey prediction method which is unitary to forecast the accuracy of the changes in the quantity of cultivated land, composition model has been improved. Besides it has a good degree of fitting the actual value. At the same time, it' s simple and easy to use.关键词
GM(1,1)模型/BP神经网络/耕地/预测Key words
GM (1,1) model/ BP neural network/ Cultivated land/ Forecasting分类
农业科技引用本文复制引用
王兵,胡月明,雷霆,赵小娟..基于GM(1,1)-BP神经网络的城市耕地数量预测研究[J].安徽农业科学,2012,40(9):5712-5714,3.
