摘要
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。
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 re-cycling and remanufacturing manufacturers and producer service demand is presented .On the basis of as-certaining 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 predic-tion model of genetic algorithm-BP neural network is proposed and finally used for training , testing data and predicting manufacturers＆#39;service demand .
出处
《工业工程》
北大核心
2014年第3期114-120,共7页
Industrial Engineering Journal
基金
国家自然科学基金资助项目(70932004)
关键词
报废汽车回收再制造
特征属性匹配
生产性服务
BP神经网络
遗传算法
end-of-life vehicle recycling and remanufacturing
feature matching
producer service
BP neural network
genetic algorithm
