Data Mining and Knowledge Discovery for Process Monitoring and Control
Data Mining and Knowledge Discovery for Process Monitoring and Control

Author: Xue Z. Wang

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 263

ISBN-13: 1447104218

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Modern computer-based control systems are able to collect a large amount of information, display it to operators and store it in databases but the interpretation of the data and the subsequent decision making relies mainly on operators with little computer support. This book introduces developments in automatic analysis and interpretation of process-operational data both in real-time and over the operational history, and describes new concepts and methodologies for developing intelligent, state space-based systems for process monitoring, control and diagnosis. The book brings together new methods and algorithms from process monitoring and control, data mining and knowledge discovery, artificial intelligence, pattern recognition, and causal relationship discovery, as well as signal processing. It also provides a framework for integrating plant operators and supervisors into the design of process monitoring and control systems.

Data Mining
Data Mining

Author:

Publisher: BoD – Books on Demand

Published: 2022-03-30

Total Pages: 226

ISBN-13: 1839692669

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The availability of big data due to computerization and automation has generated an urgent need for new techniques to analyze and convert big data into useful information and knowledge. Data mining is a promising and leading-edge technology for mining large volumes of data, looking for hidden information, and aiding knowledge discovery. It can be used for characterization, classification, discrimination, anomaly detection, association, clustering, trend or evolution prediction, and much more in fields such as science, medicine, economics, engineering, computers, and even business analytics. This book presents basic concepts, ideas, and research in data mining.

European Symposium on Computer Aided Process Engineering - 13
European Symposium on Computer Aided Process Engineering - 13

Author: Andrzej Kraslawski

Publisher: Elsevier

Published: 2003-05-07

Total Pages: 1175

ISBN-13: 0080529445

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This book contains papers presented at the 13th European Symposium on Computer Aided Process Engineering (ESCAPE-13). The ESCAPE symposia bring together scientists, students and engineers from academia and industry, who are active in the research and application of Computer Aided Process Engineering.The objective of ESCAPE-13 is to promote CAPE applications into new businesses and technologies by highlighting the use of computers and information technology tools in five specific areas: process design; process control and dynamics; modeling, simulation and optimization; applications in pulp and paper industry; and applications in biotechnology.Includes 190 papers selected from 391 submitted abstracts.All papers have been reviewed by 33 members of the international scientific community.

Predictive Analysis on Large Data for Actionable Knowledge: Emerging Research and Opportunities
Predictive Analysis on Large Data for Actionable Knowledge: Emerging Research and Opportunities

Author: Usman, Muhammad

Publisher: IGI Global

Published: 2018-01-26

Total Pages: 187

ISBN-13: 1522550305

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Data analysis forms the basis of many modes of research ranging from scientific discoveries to governmental findings. With the advent of machine intelligence and neural networks, extracting and modeling, approaching data has been unimpeachably altered. These changes, seemingly small, affect the way societies organize themselves, deliver services, or interact with each other. Predictive Analysis on Large Data for Actionable Knowledge: Emerging Research and Opportunities provides emerging information on extraction and prediction patterns in data mining along with knowledge discovery. While highlighting the current issues in data extraction, readers will learn new methodologies comprising of different algorithms that automate the multidimensional schema that remove the manual processes. This book is a vital resource for researchers, academics, and those seeking new information on data mining techniques and trends.

Knowledge-based Intelligent Information Engineering Systems & Allied Technologies
Knowledge-based Intelligent Information Engineering Systems & Allied Technologies

Author: Norio Baba

Publisher: IOS Press

Published: 2001

Total Pages: 860

ISBN-13: 9781586031923

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The annual Kes International Conference in Knowledge-based Intelligent Information Engineering Systems and Allied Technologies has become an event that is held in high regard by the intelligent systems community. The proceedings of the fifth conference represents a comprehensive survey of research on the theory and application of knowledge-based intelligent systems including topics such as: generic intelligent techniques - artificial neural networks, machine learning fuzzy and neuro-fuzzy techniques, and artificial life; applications of intelligent systems - condition monitoring, fault diagnosis, image processing, and high voltage systems; and allied technologies - communications, the Internet and web-based technologies, e-commerce, and computer pets. The proceedings should be of interest to those in the intelligent systems field, such as engineers, researchers and students.

Cluster Analysis for Data Mining and System Identification
Cluster Analysis for Data Mining and System Identification

Author: János Abonyi

Publisher: Springer Science & Business Media

Published: 2007-08-10

Total Pages: 317

ISBN-13: 376437988X

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The aim of this book is to illustrate that advanced fuzzy clustering algorithms can be used not only for partitioning of the data. It can also be used for visualization, regression, classification and time-series analysis, hence fuzzy cluster analysis is a good approach to solve complex data mining and system identification problems. This book is oriented to undergraduate and postgraduate and is well suited for teaching purposes.

Intelligent Decision Making in Quality Management
Intelligent Decision Making in Quality Management

Author: Cengiz Kahraman

Publisher: Springer

Published: 2015-10-31

Total Pages: 474

ISBN-13: 331924499X

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This book presents recently developed intelligent techniques with applications and theory in the area of quality management. The involved applications of intelligence include techniques such as fuzzy sets, neural networks, genetic algorithms, etc. The book consists of classical quality management topics dealing with intelligent techniques for solving the complex quality management problems. The book will serve as an excellent reference for quality managers, researchers, lecturers and postgraduate students in this area. The authors of the chapters are well-known researchers in the area of quality management.

Data-driven Methods for Fault Detection and Diagnosis in Chemical Processes
Data-driven Methods for Fault Detection and Diagnosis in Chemical Processes

Author: Evan L. Russell

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 193

ISBN-13: 1447104099

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Early and accurate fault detection and diagnosis for modern chemical plants can minimise downtime, increase the safety of plant operations, and reduce manufacturing costs. The process-monitoring techniques that have been most effective in practice are based on models constructed almost entirely from process data. The goal of the book is to present the theoretical background and practical techniques for data-driven process monitoring. Process-monitoring techniques presented include: Principal component analysis; Fisher discriminant analysis; Partial least squares; Canonical variate analysis. The text demonstrates the application of all of the data-driven process monitoring techniques to the Tennessee Eastman plant simulator - demonstrating the strengths and weaknesses of each approach in detail. This aids the reader in selecting the right method for his process application. Plant simulator and homework problems in which students apply the process-monitoring techniques to a nontrivial simulated process, and can compare their performance with that obtained in the case studies in the text are included. A number of additional homework problems encourage the reader to implement and obtain a deeper understanding of the techniques. The reader will obtain a background in data-driven techniques for fault detection and diagnosis, including the ability to implement the techniques and to know how to select the right technique for a particular application.

Adaptive and Natural Computing Algorithms
Adaptive and Natural Computing Algorithms

Author: Ville Kolehmainen

Publisher: Springer

Published: 2009-09-30

Total Pages: 645

ISBN-13: 3642049214

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This book constitutes the thoroughly refereed post-proceedings of the 9th International Conference on Adaptive and Natural Computing Algorithms, ICANNGA 2009, held in Kuopio, Finland, in April 2009. The 63 revised full papers presented were carefully reviewed and selected from a total of 112 submissions. The papers are organized in topical sections on neutral networks, evolutionary computation, learning, soft computing, bioinformatics as well as applications.