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What is A Neural Network Methodology For Process about?

This paper presents a neural-network-based methodology for process fault diagnosis, addressing limitations of knowledge-based expert systems (KBES) such as tedious knowledge acquisition and inability to learn dynamically. The proposed approach, demonstrated through a case study of a fluidized catalytic cracking process, effectively diagnoses known faults and generalizes to novel fault combinations while handling incomplete data. The methodology is compared to traditional KBES, highlighting its advantages in

Author

319323850

Language

EN