基于模糊神经网络的筑路机械生产率预测方法

Neural Network Model for Estimating Productivity

以高等级公路沥青混凝土面层施工机械系统为研究对象 ,提出了一种施工机械生产率的预测方法。该方法利用神经网络和模糊数学 ,通过鉴定和收集相关数据 ,设计了带有模糊输入输出系统的神经网络预测模型。该预测方法与现有的统计预测模型相比 ,使用更加简便 ,预测结果的准确性更高。该模型是针对沥青路面施工机械提出的 。

This paper describes an approach developed to estimate highway construction machine system productivity. The system utilizes artificial neural network,fuzzy,historic information and experience of manager. It find determine factors that affect labor productivity,input and output structure. The method is compared to an existing statistical model and is found to improve the quality of the estimates attained.