机器学习技术的渐进式研究和调查,以提高工业4.0的效率和有效性

Kaljot Sharma, D. Anand, K. Mishra, S. Harit
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引用次数: 2

摘要

本文的目标是通过2017年1月至2020年3月期间发表的论文,评估工业4.0的最新工作以及工业4.0的科学现状。采用系统评价流程,文章选择分为5步,包括以下步骤:1)数据库选择2)关键词研究3)文章收集4)纳入/排除标准5)选定文章检查。值得注意的是,许多研究都是哲学性的或基于案例的。本文所描述的前瞻性研究方向可能对对工业4.0领域感兴趣的研究人员有所帮助。本文未来的研究方向无疑对研究者有益。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Progressive Study and Investigation of Machine Learning Techniques to Enhance the Efficiency and Effectiveness of Industry 4.0
The goal of this article is to assess the most recent work on Industry 4.0 as well as the present state of science on Industry 4.0 through papers produced between January 2017 and March 2020.A systematic review process with a 5-step approach to article selection was employed, which included the following steps: 1) Selection of database 2) Research of keyword 3) Collection of articles 4) Inclusion/Exclusion criteria 5) Examining Selected Articles. It is noticed that much of the research is philosophical or case-based in character. The prospective study direction described in this paper may be useful to researchers interested in the field of industry 4.0 for research. The paper's future study directions must undoubtedly be beneficial to researchers.
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