混合解决未来问题的挑战,在新一代人工智能产业中运用运筹学研究工业流程

IF 2.2 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS Data Pub Date : 2021-04-05 DOI:10.1145/3460620.3460757
T. Mohammed, Mohammed N. Qasim, O. Bayat
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引用次数: 1

摘要

新一代工业系统等关键技术高度依赖于人工智能,以及能够将整个供应链数字化的电子物理系统,以及数据挖掘、机器学习等。目前,使用基于人工智能的解决方案对于提高生产过程的准确性和效率非常重要。人工智能(AI)在第四次工业革命中发挥着关键作用,我们看到不同的机器学习方法取得了重大进步。人工智能被实践性工程师广泛应用于解决各种问题。该杂志为快速描述人工智能在机械工程各个领域的实际应用的文章提供了一个国际论坛。许多研究人员引用工业领域技术的发展来减少工业中的问题。运筹学(OR)社区和人工智能(AI)都表明,这些问题仍然很有趣。而人工智能则专注于增加产量和缓解行业困难,这可能被视为未来的一场革命。人工智能技术为实际问题提供了更丰富、更灵活的呈现方式。本文介绍了工业实验室的架构以及在工业过程中使用人工智能所面临的挑战。
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Hybrid solution of challenges future problems in the new generation of the artificial intelligence industry used operations research industrial processes
Key technologies such as a new generation of industrial systems highly depends on artificial intelligence, and electronic physical systems that can digitize the entire supply chain together with data mining, machine learning, and more. At present, uses of artificial intelligence-based solutions are very important to improve the accuracy and efficiency of production processes. Artificial intelligence (AI) is playing a key role in the fourth industrial revolution, and we see significant improvements in different methods of machine learning. Artificial intelligence is widely used by practitioner engineers to solve various problems. This journal provides an international forum for quick articles that describes the practical application of artificial intelligence in all areas of mechanical engineering. Many researchers cited the development of technology in industrial fields to reduce problems in industry. Both the Operations Research (OR) community and Artificial Intelligence (AI) show that these problems are still interesting. While AI focuses linearly on increasing production and mitigating industry difficulties that may be seen as a revolution in the future. AI techniques offer a richer and more flexible presentation of real problems. The article presents the architecture of the industrial laboratory and the challenges associated with the use of artificial intelligence in industrial processes.
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来源期刊
Data
Data Decision Sciences-Information Systems and Management
CiteScore
4.30
自引率
3.80%
发文量
0
审稿时长
10 weeks
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