无监督学习的主要特点和技术

Dr. Gurpreet Singh
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摘要

机器学习(ML)已成为一种变革性技术,对各行各业的工业运营具有深远影响。本文全面分析了机器学习在工业环境中的应用和挑战。本文首先概述了机器学习的基本概念及其与工业流程的相关性。它探讨了各种 ML 技术,包括监督学习、无监督学习和强化学习,并讨论了它们在优化生产、加强质量控制和预测设备故障方面的适用性。DOI:https://doi.org/10.52783/tjjpt.v45.i02.5825
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Key Features and Techniques of Unsupervised Learning
Machine learning (ML) has emerged as a transformative technology with profound implications for industrial operations across diverse sectors. This paper provides a comprehensive analysis of the applications and challenges, of machine learning in industrial settings. The paper begins by outlining the foundational concepts of machine learning and its relevance to industrial processes. It explores various ML techniques, including supervised learning, unsupervised learning, and reinforcement learning, and discusses their applicability in optimizing production, enhancing quality control, and predicting equipment failures. DOI:https://doi.org/10.52783/tjjpt.v45.i02.5825
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