Contractor Prequalification Based on Neural Networks  

作　　者：ZHANG Jin-long, YANG Lan-rongCollege of Management, Huazhong University of Science and Technology, Wuhan 430074, China 

出　　处：《Systems Science and Systems Engineering》2002年第2期209-214,共6页系统科学与系统工程学报（英文版）

摘　　要：Contractor Prequalification involves the screening of contractors by a project owner, according to a given set of criteria, in order to determine their competence to perform the work if awarded the construction contract. This paper introduces the capabilities of neural networks in solving problems related to contractor prequalification. The neural network systems for contractor prequalification has an input vector of 8 components and an output vector of 1 component. The output vector represents whether a contractor is qualified or not qualified to submit a bid on a project.Contractor Prequalification involves the screening of contractors by a project owner, according to a given set of criteria, in order to determine their competence to perform the work if awarded the construction contract. This paper introduces the capabilities of neural networks in solving problems related to contractor prequalification. The neural network systems for contractor prequalification has an input vector of 8 components and an output vector of 1 component. The output vector represents whether a contractor is qualified or not qualified to submit a bid on a project.

关 键 词：PREQUALIFICATION neural networks 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程]