基于AHP和动量BP神经网络的工程项目承包商选择模型

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.

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

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.