Advanced data-driven approaches for modelling and classification: with applications to automotive engine fault detection and polymer extrusion control - Softcover

Deng, Jing

Softcover

ISBN 10: 3659301418 ISBN 13: 9783659301414

Publisher: LAP LAMBERT Academic Publishing, 2012

Synopsis

In this book, the Fast Recursive Algorithm (FRA) and Two-Stage Selection (TSS) methods proposed by Prof. Li and Prof. Irwin have been improved to integrate Bayesian regularisation to prevent over-fitting and leave-one-out cross validation for automatic model construction. To further enhance model generalization capability, some heuristic methods were also embedded in the two-stage selection to optimize the non-linear parameters involved in subset model construction. These include Particle Swarm Optimization (PSO), Defferential Evolution (DE), and Extreme Learning Machine (ELM). The effectiveness and efficiency of all these advanced methods have been confirmed on both well-known benchmarks and real world data sets from automotive engine and polymer extrusion applications.

About this title

About the Author

Dr Jing Deng received his B.Sc.degree from National University of Defence Technology, Hunan, China, in 2005, the M.Sc.degrees from the Shanghai University, Shanghai, China, in 2007, and the Ph.D. degree from the Intelligent Systems and Control(ISAC) Group at Queen’s University Belfast,UK in 2011. From then, he worked as a research Fellow at QUB.

Edition details

• Publisher: LAP LAMBERT Academic Publishing
• Publication date: 2012
• Language: English
• ISBN 10: 3659301418
• ISBN 13: 9783659301414
• Binding: Paperback
• Number of pages: 160