摘要
本文针对当前国内外对产品质量标准数据清洗问题研究的局限,基于人工智能学科中的BP人工神经网络理论,用L-M算法改进的BP人工神经网络构建了产品质量标准数据清洗模型,并以洗衣机产品质量标准数据为实例,用所设计模型进行了产品质量标准数据清洗实验验证。经实验验证发现,本研究给出的模型是一种具有普适意义、符合科学理论、合理的产品质量标准数据清洗模型,支持绝大部分产品质量标准数据清洗,既丰富了产品质量标准数据清洗理论,又能应用于经济社会发展实践。模型支持产品质量标准数据自动化、智能化、高速度清洗,为国家质量基础设施(NQI)共性技术的研究提供了重要的方法论。
Aiming at the limitation of research on data cleaning of product quality standard at home and abroad, based on the theory of BP artificial neural network in the subject of artificial intelligence, this paper constructs the data cleaning model of product quality standard with BP artificial neural network improved by L-M algorithm, and takes the product quality standard data of washing machine as an example, and the designed model is used to test the data cleaning of product quality standard. The experimental results show that the data cleaning model of product quality standard given in this study is a universal, scientific and reasonable data cleaning model of product quality standard, which supports most of the data cleaning of product quality standard, not only enriches the theory of data cleaning of product quality standard, but also applies to the practice of economic and social development. The model supports automatic, intelligent and high-speed cleaning of product quality standard data, and provides an important methodology for the research of National Quality Infrastructure(NQI) common technology.
作者
王兆君
岳良文
WANG Zhao-jun;YUE Liang-wen(Beijing SunwayWorld Science&Technology Co.,Ltd.)
出处
《标准科学》
2020年第4期88-95,共8页
Standard Science
基金
国家重点研发计划项目“’互联网+'NQI集成服务共性技术研究”(项目编号:2017YFF0209600)
“NQI集成服务基础理论和通用标准研究”(项目编号:2017YFF0209601)
“NQI集成服务关键应用技术研究”(项目编号:2017YFF0209603)资助。
关键词
人工神经网络
L-M算法
国家质量基础设施
质量标准
数据清洗模型
artificial neural network
L-M algorithm
national quality infrastructure
quality standard
data cleaning model
