Get all the updates for this publication
Articles
A hybrid methodology for on-line process monitoringPublished in Berkeley Electronic Press
2004
Volume: 2
A hybrid strategy of using (i) locally linear embedding for nonlinear dimensionality reduction of high dimensional data and (ii) support vector machines for classification of the resultant features is proposed as a robust methodology for process monitoring. Illustrative examples substantiate the methodology vis-à-vis current practice.
Topics: Support vector machine (52)%52% related to the paper and Nonlinear dimensionality reduction (52)%52% related to the paper
View more info for "A Hybrid Methodology For On-Line Process Monitoring"
Publisher Copy Version
Content may be subject to copyright.Originally published at https://doi.org/10.2202/1542-6580.1119Originally published at https://doi.org/10.2202/1542-6580.1119
About the journal
Published in Berkeley Electronic Press
Open Access
noImpact factor
N/AAuthors (1)
Valadi Krishnamoorthy Jayaraman- A Simple Method of Solution For Multi-label Feature Selection
- Applications of artificial intelligence and machine learning in viral biology
- AllerBase: a comprehensive allergen knowledgebase
- Identification of Glucose-Binding Pockets in Human Serum Albumin Using Support Vector Machine and Molecular Dynamics Simulations
