A Nonlinear Support Vector Machine-Based Feature Selection Approach for Fault Detection and Diagnosis: Application to the Tennessee Eastman Process

Lignende værker

• Simultaneous Fault Detection and Identification in Continuous Processes via nonlinear Support Vector Machine based Feature Selection
  af: Onel, Melis, et al.
  Udgivet: (2018)
• Big Data Approach to Batch Process Monitoring: Simultaneous Fault Detection and Diagnosis Using Nonlinear Support Vector Machine-based Feature Selection
  af: Onel, Melis, et al.
  Udgivet: (2018)
• Fault Diagnosis of Tennessee Eastman Process with XGB-AVSSA-KELM Algorithm
  af: Mingfei Hu, et al.
  Udgivet: (2022-04-01)
• Fault diagnosis of Tennessee Eastman process using signal geometry matching technique
  af: Li Han, et al.
  Udgivet: (2011-01-01)
• Fault Diagnosis for Wireless Sensor by Twin Support Vector Machine
  af: Mingli Ding, et al.
  Udgivet: (2013-01-01)