基于模糊神经网络的土地合理储备量预测研究

基金项目: 武汉大学优秀博士论文培育基金资助项目(虚拟地理环境平台研究与开发)

详细信息

Application of Fuzzy Neural Networks to Land Reserve Prediction

¹ School of Resource and Environment Science,Wuhan University,129 Luoyu Road,Wuhan 430079,China; ² School of River & Ocean,Chongqing Jiaotong University,66 Xuefu Road,Chongqing 400074,China

Funds: 武汉大学优秀博士论文培育基金资助项目(虚拟地理环境平台研究与开发)

摘要: 将神经网络和模糊理论相结合建立模糊神经网络模型,从模糊神经网络角度并运用灰色系统理论对建设用地量进行预测,并应用于重庆市2005~2010年的建设用地量预测。计算分析结果表明,该模型具有良好的可行性和合理性,可以为确定土地合理储备量提供依据。
- 土地储备 /
- 建设用地 /
- 补偿模糊神经网络 /
- 灰色模型
Abstract: It is an important problem to decide the reasonable quantity for land reserve.The model of fuzzy neural network is established by combining neural network with fuzzy theory.In view of fuzzy neural network,the quantity of construction land is predicted by use of grey system theory.The prediction of ChongQing City's construction land quantity from 2005 to 2010 is used as an example for this method.
- land reserve /
- construction land /
- fuzzy neural network /
- grey model