Statistical Process Monitoring Using Advanced Data Driven And Deep Learning Approaches

Author : Fouzi Harrou
Publisher : Elsevier
ISBN 13 : 0128193662
Total Pages : 330 pages
Book Rating : 4.62/5 ( download)

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Download or read book Statistical Process Monitoring Using Advanced Data-Driven and Deep Learning Approaches written by Fouzi Harrou and published by Elsevier. This book was released on 2020-07-03 with total page 330 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical Process Monitoring Using Advanced Data-Driven and Deep Learning Approaches tackles multivariate challenges in process monitoring by 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. Uses a data-driven based approach to fault detection and attribution Provides an in-depth understanding of fault detection and attribution in complex and multivariate systems Familiarises you with the most suitable data-driven based techniques including multivariate statistical techniques and deep learning-based methods Includes case studies and comparison of different methods

Author : Fouzi Harrou
Publisher : Elsevier
ISBN 13 : 0128234334
Total Pages : 270 pages
Book Rating : 4.34/5 ( download)

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Download or read book Road Traffic Modeling and Management written by Fouzi Harrou and published by Elsevier. This book was released on 2021-10-05 with total page 270 pages. Available in PDF, EPUB and Kindle. Book excerpt: Road Traffic Modeling and Management: Using Statistical Monitoring and Deep Learning provides a framework for understanding and enhancing road traffic monitoring and management. The book examines commonly used traffic analysis methodologies as well the emerging methods that use deep learning methods. Other sections discuss how to understand statistical models and machine learning algorithms and how to apply them to traffic modeling, estimation, forecasting and traffic congestion monitoring. Providing both a theoretical framework along with practical technical solutions, this book is ideal for researchers and practitioners who want to improve the performance of intelligent transportation systems. Provides integrated, up-to-date and complete coverage of the key components for intelligent transportation systems: traffic modeling, forecasting, estimation and monitoring Uses methods based on video and time series data for traffic modeling and forecasting Includes case studies, key processes guidance and comparisons of different methodologies

Author : Flavio Manenti
Publisher : Elsevier
ISBN 13 : 0443288259
Total Pages : 3634 pages
Book Rating : 4.58/5 ( download)

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Download or read book 34th European Symposium on Computer Aided Process Engineering /15th International Symposium on Process Systems Engineering written by Flavio Manenti and published by Elsevier. This book was released on 2024-06-28 with total page 3634 pages. Available in PDF, EPUB and Kindle. Book excerpt: The 34th European Symposium on Computer Aided Process Engineering / 15th International Symposium on Process Systems Engineering, contains the papers presented at the 34th European Symposium on Computer Aided Process Engineering / 15th International Symposium on Process Systems Engineering joint event. It is a valuable resource for chemical engineers, chemical process engineers, researchers in industry and academia, students, and consultants for chemical industries. Presents findings and discussions from the 34th European Symposium on Computer Aided Process Engineering / 15th International Symposium on Process Systems Engineering joint event

Author : Hassan Haes Alhelou
Publisher : Springer Nature
ISBN 13 : 3031203607
Total Pages : 463 pages
Book Rating : 4.02/5 ( download)

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Download or read book Power Systems Cybersecurity written by Hassan Haes Alhelou and published by Springer Nature. This book was released on 2023-03-12 with total page 463 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers power systems cybersecurity. In order to enhance overall stability and security in wide-area cyber-physical power systems and defend against cyberattacks, new resilient operation, control, and protection methods are required. The cyberattack-resilient control methods improve overall cybersecurity and stability in normal and abnormal operating conditions. By contrast, cyberattack-resilient protection schemes are important to keep the secure operation of a system under the most severe contingencies and cyberattacks. The main subjects covered in the book are: 1) proposing new tolerant and cyberattack-resilient control and protection methods against cyberattacks for future power systems, 2) suggesting new methods for cyberattack detection and cybersecurity assessment, and 3) focusing on practical issues in modern power systems.

Author : Didier Theilliol
Publisher : Springer Nature
ISBN 13 : 3031275403
Total Pages : 352 pages
Book Rating : 4.01/5 ( download)

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Download or read book Recent Developments in Model-Based and Data-Driven Methods for Advanced Control and Diagnosis written by Didier Theilliol and published by Springer Nature. This book was released on 2023-07-15 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book consists of recent works on several axes either with a more theoretical nature or with a focus on applications, which will span a variety of up-to-date topics in the field of systems and control. The main market area of the contributions include: Advanced fault-tolerant control, control reconfiguration, health monitoring techniques for industrial systems, data-driven diagnosis methods, process supervision, diagnosis and control of discrete-event systems, maintenance and repair strategies, statistical methods for fault diagnosis, reliability and safety of industrial systems artificial intelligence methods for control and diagnosis, health-aware control design strategies, advanced control approaches, deep learning-based methods for control and diagnosis, reinforcement learning-based approaches for advanced control, diagnosis and prognosis techniques applied to industrial problems, Industry 4.0 as well as instrumentation and sensors. These works constitute advances in the aforementioned scientific fields and will be used by graduate as well as doctoral students along with established researchers to update themselves with the state of the art and recent advances in their respective fields. As the book includes several applicative studies with several multi-disciplinary contributions (deep learning, reinforcement learning, model-based/data-based control etc.), the book proves to be equally useful for the practitioners as well industrial professionals.

Author : Chung Siung Choo
Publisher : Springer Nature
ISBN 13 : 9819955475
Total Pages : 321 pages
Book Rating : 4.73/5 ( download)

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Download or read book Proceedings of ASEAN-Australian Engineering Congress (AAEC2022) written by Chung Siung Choo and published by Springer Nature. This book was released on 2023-12-19 with total page 321 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the proceedings of the ASEAN-Australian Engineering Congress (AAEC2022), held as a virtual event, 13–15 July 2022 with the theme “Engineering Solutions in the Age of Digital Disruption”. The book presents selected papers covering scientific research in the field of Engineering Computing, Network, Communication and Cybersecurity, Artificial Intelligence & Machine Learning, Materials Science & Manufacturing, Automation and Sensors, Smart Energy & Cities, Simulation & Optimisation and other Industry 4.0 related Technologies. The book appeals to researchers, academics, scientists, students, engineers and practitioners who are interested in the latest developments and applications related to addressing the Fourth Industrial Revolution (IR4.0).

Author : Olfa Kanoun
Publisher : Springer Nature
ISBN 13 : 3030712214
Total Pages : 291 pages
Book Rating : 4.11/5 ( download)

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Download or read book Advanced Systems for Biomedical Applications written by Olfa Kanoun and published by Springer Nature. This book was released on 2021-07-19 with total page 291 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book highlights recent developments in the field of biomedical systems covering a wide range of technological aspects, methods, systems and instrumentation techniques for diagnosis, monitoring, treatment, and assistance. Biomedical systems are becoming increasingly important in medicine and in special areas of application such as supporting people with disabilities and under pandemic conditions. They provide a solid basis for supporting people and improving their health care. As such, the book offers a key reference guide about novel medical systems for students, engineers, designers, and technicians.

Author : Ch. Venkateswarlu
Publisher : Elsevier
ISBN 13 : 0323900682
Total Pages : 400 pages
Book Rating : 4.83/5 ( download)

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Download or read book Optimal State Estimation for Process Monitoring, Fault Diagnosis and Control written by Ch. Venkateswarlu and published by Elsevier. This book was released on 2022-01-31 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt: Optimal State Estimation for Process Monitoring, Fault Diagnosis and Control presents various mechanistic model based state estimators and data-driven model based state estimators with a special emphasis on their development and applications to process monitoring, fault diagnosis and control. The design and analysis of different state estimators are highlighted with a number of applications and case studies concerning to various real chemical and biochemical processes. The book starts with the introduction of basic concepts, extending to classical methods and successively leading to advances in this field. Design and implementation of various classical and advanced state estimation methods to solve a wide variety of problems makes this book immensely useful for the audience working in different disciplines in academics, research and industry in areas concerning to process monitoring, fault diagnosis, control and related disciplines. Describes various classical and advanced versions of mechanistic model based state estimation algorithms Describes various data-driven model based state estimation techniques Highlights a number of real applications of mechanistic model based and data-driven model based state estimators/soft sensors Beneficial to those associated with process monitoring, fault diagnosis, online optimization, control and related areas

Author : Chris Aldrich
Publisher : Springer Science & Business Media
ISBN 13 : 1447151852
Total Pages : 388 pages
Book Rating : 4.52/5 ( download)

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Download or read book Unsupervised Process Monitoring and Fault Diagnosis with Machine Learning Methods written by Chris Aldrich and published by Springer Science & Business Media. This book was released on 2013-06-15 with total page 388 pages. Available in PDF, EPUB and Kindle. Book excerpt: This unique text/reference describes in detail the latest advances in unsupervised process monitoring and fault diagnosis with machine learning methods. Abundant case studies throughout the text demonstrate the efficacy of each method in real-world settings. The broad coverage examines such cutting-edge topics as the use of information theory to enhance unsupervised learning in tree-based methods, the extension of kernel methods to multiple kernel learning for feature extraction from data, and the incremental training of multilayer perceptrons to construct deep architectures for enhanced data projections. Topics and features: discusses machine learning frameworks based on artificial neural networks, statistical learning theory and kernel-based methods, and tree-based methods; examines the application of machine learning to steady state and dynamic operations, with a focus on unsupervised learning; describes the use of spectral methods in process fault diagnosis.

Author : ALIREZA. BEHKAMAL ENTEZAMI (BAHAREH. DE MICHELE, CARLO.)
Publisher : Springer Nature
ISBN 13 : 3031539958
Total Pages : 123 pages
Book Rating : 4.54/5 ( download)

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Download or read book Long-term Structural Health Monitoring by Remote Sensing and Advanced Machine Learning written by ALIREZA. BEHKAMAL ENTEZAMI (BAHAREH. DE MICHELE, CARLO.) and published by Springer Nature. This book was released on 2024 with total page 123 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers an in-depth investigation into the complexities of long-term structural health monitoring (SHM) in civil structures, specifically focusing on the challenges posed by small data and environmental and operational changes (EOCs). Traditional contact-based sensor networks in SHM produce large amounts of data, complicating big data management. In contrast, synthetic aperture radar (SAR)-aided SHM often faces challenges with small datasets and limited displacement data. Additionally, EOCs can mimic the structural damage, resulting in false errors that can critically affect economic and safety issues. Addressing these challenges, this book introduces seven advanced unsupervised learning methods for SHM, combining AI, data sampling, and statistical analysis. These include techniques for managing datasets and addressing EOCs. Methods range from nearest neighbor searching and Hamiltonian Monte Carlo sampling to innovative offline and online learning frameworks, focusing on data augmentation and normalization. Key approaches involve deep autoencoders for data processing and novel algorithms for damage detection. Validated using simulated data from the I-40 Bridge, USA, and real-world data from the Tadcaster Bridge, UK, these methods show promise in addressing SAR-aided SHM challenges, offering practical tools for real-world applications. The book, thereby, presents a comprehensive suite of innovative strategies to advance the field of SHM.