[1]叶青.厦门市工程估价的RBF神经网络预测模型[J].华侨大学学报(自然科学版),2012,33(4):446-450.[doi:10.11830/ISSN.1000-5013.2012.04.0446]
　YE Qing.Prediction Model of the Project Cost Estimation Based on RBF Neural Network[J].Journal of Huaqiao University(Natural Science),2012,33(4):446-450.[doi:10.11830/ISSN.1000-5013.2012.04.0446]
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厦门市工程估价的RBF神经网络预测模型()
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《华侨大学学报（自然科学版）》[ISSN:1000-5013/CN:35-1079/N]

卷:
第33卷
期数:
2012年第4期
页码:
446-450
栏目:
出版日期:
2012-07-20

文章信息/Info

Title:
Prediction Model of the Project Cost Estimation Based on RBF Neural Network
文章编号:
1000-5013(2012)04-0446-05
作者:
叶青
华侨大学 土木工程学院, 福建 厦门 361021
Author(s):
YE Qing
College of Civil Engineering, Huaqiao University, Xiamen 361021, China
关键词:
工程估价;  预测模型;  径向基函数;  人工神经网络;  厦门市
Keywords:
project cost estimation;  prediction model;  radial basis function;  artificial neural network;  Xiamen city
分类号:
TU723.3;TP183
DOI:
10.11830/ISSN.1000-5013.2012.04.0446
文献标志码:
A
摘要:
选取55个厦门市典型工程造价指标,利用SPSS统计分析软件对工程特征和训练样本进行相关性分析、归类合并,得出11个工程特征作为平米造价的主要影响因素.以径向基函数(RBF)神经网络原理为基础,建立工程造价估算模型,通过试验,选择net=newrb(P,T,0.01,1.0)建立RBF网络,用y=sim(net1,P)对样本进行训练测试.实证分析结果显示:该模型具有计算快捷简便的优势,估算误差在允许范围内,可用于实际工程造价的辅助估算.
Abstract:
55 typical engineering cost indexes in Xiamen city were selected and analyzed, to obtain the correlation of engineering features and training samples by SPSS statistical analysis software. Based on radial basis function(RBF)neural network theory, the project cost estimation model is established. Selecting the net=newrb(P,T,0.01,1.0)to establish RBF network through the test, using y=sim(net1,P)to train and test, the calculation results show that the model has the advantage of convenient calculation, the estimation error is small and allowable, and the model is worth in the project prediction estimation.

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期: 2011-11-09
通信作者: 叶青(1968-),女,教授,主要从事工程造价和房地产价格评估的研究.E-mail:yeqing@hqu.edu.cn.
基金项目: 中央高校基本科研业务费专项资金资助项目(JB-ZR1162); 福建省泉州市科技计划项目(2009Z52); 华侨大学高层次人才科研启动项目(12BS131)
更新日期/Last Update: 2012-07-20