论文标题
部分可观测时空混沌系统的无模型预测
Modern Machine Learning Tools for Monitoring and Control of Industrial Processes: A Survey
论文作者
论文摘要
在过去的十年中，我们看到了工业数据，计算能力的巨大改善以及机器学习的重大理论进步。这为在大规模的非线性监控和控制问题上使用现代机器学习工具提供了机会。本文对过程行业的应用进行了对最新结果的调查。
Over the last ten years, we have seen a significant increase in industrial data, tremendous improvement in computational power, and major theoretical advances in machine learning. This opens up an opportunity to use modern machine learning tools on large-scale nonlinear monitoring and control problems. This article provides a survey of recent results with applications in the process industry.
