Statistical Process Monitoring Using Advanced Data-Driven and Deep Learning Approaches: Theory and Practical Applications

Statistical Process Monitoring Using Advanced Data-Driven and Deep Learning Approaches: Theory and Practical Applications
By 作者:Fouzi Harrou (Author), Ying Sun (Author), Amanda S. Hering (Author), Muddu Madakyaru (Author), abdelkader Dairi (Author)
pages 页数: 328 pages
ISBN-10 : 0128193654
ISBN-13 : 9780128193655
Product Dimensions : 15.24 x 1.75 x 22.86 cm
Publisher Finelybook 出版社 : Elsevier (18 July 2020)
Language 语言: : English

The Book Description robot was collected from Amazon and arranged by Finelybook
Statistical Process Monitoring Using Advanced Data-Driven and Deep Learning Approaches tackles multivariate challenges in process monitoring By 作者:merging the advantages of univariate and traditional multivariate techniques to enhance their performance and widen their practical applicability. The book proceeds with merging the desirable properties of shallow learning approaches – such as a one-class support vector machine and k-nearest neighbours and unsupervised deep learning approaches – to develop more sophisticated and efficient monitoring techniques.
Finally, the developed approaches are applied to monitor many processes, such as waste-water treatment plants, detection of obstacles in driving environments for autonomous robots and vehicles, robot swarm, chemical processes (continuous stirred tank reactor, plug flow rector, and distillation columns), ozone pollution, road traffic congestion, and solar photovoltaic systems.