摘要
根据我国制造业发展的现状以及相关部门出台的关于我国制造业现阶段提升设计能力的相关指标和数据,对制造业的30个产业的设计能力进行研究。以反应我国制造业设计能力的13个指标原始数据,通过对30个样本进行数据拟合,基于RBF神经网络构建了我国制造业设计能力评价模型,根据该模型对我国制造业进行设计能力进行了评价。结果表明,与其他神经网络相比,RBF神经网络的泛化能力强,模型精度高;并从6个方面对我国制造业设计能力提升提出了建议,为制造业相关企业和政府部门提供决策参考。
According to the status quo of my country’s manufacturing industry and relevant indicators and data released by related departments on the improvement of design capabilities of my country’s manufacturing industry at this stage,the design capabilities of 30 industries in the manufacturing industry are studied.Based on the original data of 13 indicators reflecting the design capability of my country’s manufacturing industry,through data fitting of 30 samples,an evaluation model of my country’s manufacturing design capability is constructed based on the RBF neural network.According to this model,the design capability of my country’s manufacturing Evaluation.The results show that compared with other neural networks,the RBF neural network has strong generalization ability and high model accuracy;it also provides suggestions for improving the design capacity of my country’s manufacturing industry from six aspects,and provides decision-making reference for manufacturing-related enterprises and government branch.
作者
韩鹏
余开朝
HAN Peng;YU Kaichao(College Faculty of Mechanical and Electrical Engineering Kunming University of Science and Technology,Kunming Yunnan 650500)
出处
《软件》
2021年第2期11-14,34,共5页
Software
基金
云南智能化自动化产业发展研究(YNDR2017G1C06)。
关键词
中国制造业
设计能力
RBF神经网络
能力评价
chinese manufacturing
designing ability
RBF neural network
ability evaluation
