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Springer Dynamic Modeling of Complex Industrial Processes: Data-driven Methods and Application Research (Springer Theses)

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Description

Nominated as an outstanding PhD thesis by Tsinghua University Develops a systematic, data-based dynamic modeling framework for industrial processes in keeping with the slowness principle Proposes an effective process monitoring strategy to eliminate false alarms in industrial production Presents a holistic framework for adaptive process monitoring system design Offers dynamic quality prediction models with improved data utilization and accuracy for product quality control

Product Specifications

Format
paperback
Domain
Amazon UK
Release Date
30 January 2019
Listed Since
30 January 2019

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