报废汽车回收再制造企业特征属性与生产性服务需求匹配预测

为了应对报废汽车回收再制造行业的快速发展，将报废汽车回收再制造产业链与生产服务相结合，提出将报废汽车回收再制造企业特征参数与多种生产性服务进行匹配的预测模型。通过调查问卷方式获得原始样本数据，并采用主成分分析方法进行数据处理，建立遗传算法 BP神经网络混合模型，然后对模型进行训练和测试，实现对生产性服务需求匹配的预测功能。

Prediction of Feature Matching Between End-of-Life Vehicle Recycling and Remanufacturing Manufacturers and Producer Service Demand

With the rapid development of the China automobile recycling and remanufacturing market, a BP neural network and genetic algorithm mixed model for featuring matching between end-of-life vehicle recycling and remanufacturing manufacturers and producer service demand is presented. On the basis of ascertaining the feature parameters and collecting data through questionnaire, principal component analysis is used to eliminate information overlapping of the raw data and reduce the input dimension. Then, a prediction model of genetic algorithm-BP neural network is proposed and finally used for training, testing data and predicting manufacturers-service demand.