基于AHP和动量BP神经网络的工程项目承包商选择模型  

Contractor Selection Model for Engineering Projects Based on AHP and Momentum BP Neural Network

作　　者：张熠[1] 王先甲[2] 

机构地区：[1]湖北工业大学管理学院,湖北武汉430068 [2]武汉大学经济与管理学院,湖北武汉430072

出　　处：《数学的实践与认识》2014年第21期52-57,共6页Mathematics in Practice and Theory

基　　金：教育部人文社会科学研究青年基金(14YJC630201)

摘　　要：运用BP神经网络技术,采用动量BP算法,构建了基于动量BP神经网络的工程项目承包商选择模型,并将AHP的评价结果作为学习样本,对BP神经网络模型进行训练和测试.结果表明,基于AHP和动量BP神经网络的工程项目承包商选择模型是可行的,该模型具有较高的自组织、自适应和自学习能力以及较强的容错功能,能够为一般的工程项目承包商选择活动提供有效的参考和依据.Application of BP neural network technology and momentum BP algorithm made contractor selection model for engineering projects based on momentum BP neural network. BP neural network was trained and tested by the learning sample that was attained by AHP. The results show that the model possesses high abilities of self-organization, self-adaptation and self-learning and strong function of fault tolerance, providing effective reference and basis in contractor selection activity for a general engineering project.

关 键 词：层次分析法 动量BP神经网络 工程项目 承包商选择 

分 类 号：F284[经济管理—国民经济] TU723.2[建筑科学—建筑技术科学] TP183[自动化与计算机技术—控制理论与控制工程]