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首页> 外文期刊>The Journal of the Textile Institute. Part 3, Technologies for a New Century >Natural Computation and Process Modeling in the High-performance Fiber Plant
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Natural Computation and Process Modeling in the High-performance Fiber Plant

机译:高性能纤维工厂中的自然计算和过程建模

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摘要

Modern fiber processes are capable of generating huge amounts of process data, especially with the increased use of in-line sensors, chemical analyzers and instrumentation. The driving force for such measurements is the potential use in process control and product quality assessment. Process response databases are often extremely large in size, highly complex and non-selective. Novel adaptive learning techniques like artificial neural networks may provide a solution to assimilate on-line measured process- and property-data to relevant information, in order to maintain the process under control. In this century, advanced statistical techniques and new adaptive computation techniques will be the leading techniques in data analysis and will become an essential part of daily operations in the high-performance fiber plant.
机译:现代纤维工艺能够产生大量的工艺数据,尤其是随着在线传感器,化学分析仪和仪器的使用增加。此类测量的驱动力是在过程控制和产品质量评估中的潜在用途。过程响应数据库通常规模非常大,高度复杂且具有非选择性。像人工神经网络这样的新型自适应学习技术可以提供一种将在线测量的过程和特性数据同化为相关信息的解决方案,以使过程保持受控状态。在本世纪,先进的统计技术和新的自适应计算技术将成为数据分析的领先技术,并将成为高性能纤维工厂日常运营的重要组成部分。

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