基于人工神经网络的多指标综合评价方法研究

研究了利用误差反向传播人工神经网络(BP网络)的多指标综合评价问题，并以建设工程项目招标评标为背景，建立了相应的多指标综合评价BP模型。引入附加动量法和变步长算法对BP网络算法进行改造，大大提高了标准BP神经网络收敛速度与学习训练速度，为解决多指标综合评价问题提供了一条有效途径。

Research on multiple attribute synthetical evaluation methods based on artificial neural network

The multiple attribute synthetical evaluation problems with error back propagation training artificial neural network (BP neural network) is researched. To comment the mark is the background to invite tenders by the construction project item, BP' s models of the multiple attribute syntherical evaluation have been established . The BP neural network algorithm has been transformed by lead into the additional momentum law and turn length of stride algorithm, the convergence speed and study training speed has been greatly raised, and it provides an effective approach to solving the problem of multiple attribute synthetical evaluation.