质量洞察:质量工程中活动网络的人工神经网络和分类分析

Q4 Engineering

International Journal of Quality Engineering and Technology Pub Date : 2018-01-01 DOI:10.1504/IJQET.2018.10018453

A. Badiru

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引用次数: 1

摘要

人工智能(AI)的复苏和进步激发了新的研究兴趣，将20世纪90年代的成熟技术应用或重新应用于商业和工业中的挑战。质量工程和技术领域特别适合人工智能技术的应用。质量工程计划是在由特定活动组成的经常性质量项目上进行预测的。对这些活动的适当管理是任何质量计划成功的先决条件。本文探讨了人工神经网络技术在质量项目管理活动网络中的应用。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Quality insights: artificial neural network and taxonomical analysis of activity networks in quality engineering

The resurgence and advancement of artificial intelligence (AI) has spurred new research interests in applying or re-applying proven techniques from the 1990s to challenges in business and industry. The area of quality engineering and technology is particularly amenable to the application of AI techniques. Quality engineering programs are predicted on recurring quality projects that are made up of specific activities. The proper management of such activities is a precursor for the success of any quality program. This research paper explores the application of the proven technique of artificial neural network to activity networking in the management of quality programs.

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来源期刊

International Journal of Quality Engineering and Technology Engineering-Safety, Risk, Reliability and Quality

CiteScore

0.40

自引率

0.00%

发文量

期刊介绍： IJQET fosters the exchange and dissemination of research publications aimed at the latest developments in all areas of quality engineering. The thrust of this international journal is to publish original full-length articles on experimental and theoretical basic research with scholarly rigour. IJQET particularly welcomes those emerging methodologies and techniques in concise and quantitative expressions of the theoretical and practical engineering and science disciplines.