摘要
制造业转型升级是一项长期而复杂的系统工程。本文以云南省制造业企业为主要研究对象,以云南省"2017年新一轮工业转型升级项目1000个新开工项目"为基础,从中选择了部分具有代表性的企业,从内部影响因素和外部影响因素两个方面选取指标构建影响因素评价体系,利用经遗传算法优化的BP神经网络,构建出制造业转型升级影响因素评价指标模型,并使用MATLAB数学软件对所构建模型进行训练和测试,得出云南省制造业转型升级的主要制约因素,并据此提出相应建议。
The transformation and upgrading of manufacturing industry is a longterm and complicated system engineering.The thesis focused on the manufacturing enterprises in Yunnan Province as the main research object, Based on the ＂1000 new projects of industrial transformation and upgrading in 2017＂ in Yunnan, some representa tive enterprises were selected. From the two aspects of internal and external factors setup an evaluation index sys tem for factors affecting manufacturing transformation and upgrading. Used the Genetic Algorithm to optimize the BP neural network, built the evaluation index model of factors affecting the transformation and upgrading of manu facturing industry, and used mathematical software MATLAB to build the model for training and testing. Obtained the main constraints of the transformation and upgrading of manufacturing in Yunnan Province, and corresponding suggestions were made accordingly.
作者
王鹏飞
李洋洋
余开朝
徐雪
WANG Peng-fei, LI Yang-yang, YU Kai-chao, XU Xue(College of Mechanical and Electrical Engineering, Kunming University of Science and Technology, Kunming, Yunnan 65000)
出处
《软件》
2018年第9期127-132,共6页
Software
关键词
制造业
转型升级
影响因素
转型策略
BP神经网络
Manufacturing
Transformation and upgrading
Influencing factors
Transformation strategy
BPneural network
