基于遗传神经网络的城镇基准地价评估应用——以广西灌阳县为例  

Application of Evaluating Urban Standard Land Price Based on Genetic Neural Network Algorithm——A case study of Guanyang county in Guangxi

作　　者：覃开贤[1] 何志明[1] 胡宝清[2] 

机构地区：[1]广西经贸职业技术学院,广西南宁530021 [2]广西师范学院资源与环境科学学院,南宁530001

出　　处：《广西师范学院学报（自然科学版）》2012年第1期98-103,共6页Journal of Guangxi Teachers Education University(Natural Science Edition)

基　　金：国家自然科学基金(40871250);广西自然科学基金项目(0832021Z);广西教育厅资助项目(201012MS257);广西高校优秀人才资助计划项目(2011)

摘　　要：提出了一种融合遗传算法与BP神经网络的城镇基准地价评估模型。该模型以正方形网格作为基本评价单元,以遗传算法优化BP神经网络连接权值,以BP神经网络训练样本数据,实现其他网格地价的模拟与预测。结果表明,遗传算法可以有效增强BP神经网络快速学习网络权值能力和克服收敛速度慢、易陷入局部极小值等问题,BP神经网络的网络训练学习与自适应性符合处于动态变化的土地价格发展要求,呈现出广阔的应用前景。A combination of genetic algorithm and BP neural network evaluation model of urban standard land price is presented.Based on a square grid as the basic evaluation unit,the genetic algorithm to optimize BP neural network connection weights to BP neural network training sample data,the model realizes other land grid simulation and prediction.The results show that genetic algorithm can effectively enhance the BP neural network ability to quickly learn network weights and to overcome slow convergence,and is easy to fall into local minimum problems,BP neural network learning and adaptive network training in keeping with the dynamic changes in land prices development requirements,which has a broad applied prospects.

关 键 词：遗传算法 BP神经网络 网格 地价 

分 类 号：F301.3[经济管理—产业经济]