Robust process monitoring methodology for detection and diagnosis of unobservable faults
This paper presents a new integrated methodology for fault detection and diagnosis. The
methodology is built using the multivariate exponentially weighted moving average principal …
methodology is built using the multivariate exponentially weighted moving average principal …
Multiclass data classification using fault detection-based techniques
Multiclass classification of big data is a subject of broad interest in machine learning
research nowadays, where it is necessary to extract important features from a dataset's …
research nowadays, where it is necessary to extract important features from a dataset's …
Multi-objective optimization based recursive feature elimination for process monitoring
Process monitoring helps to estimate the quality of the end products, equipment health
parameters, and operational reliability of chemical processes. This is an area in which data …
parameters, and operational reliability of chemical processes. This is an area in which data …
Optimization of Unmanned Aerial Vehicle Flight Control Sensor Control System based on Deep Learning Model
J Liu - Scalable Computing: Practice and Experience, 2024 - scpe.org
Based on data modelling strategies have created reliable classifier designs for various
classes and other neural network applications. The fact that modelling complexity rises with …
classes and other neural network applications. The fact that modelling complexity rises with …
Multivariate data-based safety analysis in digitalized process systems
MT Amin - 2022 - research.library.mun.ca
Chemical process industries are vulnerable to accidents due to their inherent hazardous
nature, complex operations, and growing size. Although the control system works as the first …
nature, complex operations, and growing size. Although the control system works as the first …