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Author: Xue Z Wang
Publisher:
Published: 1999-10-15
Total Pages: 272
ISBN-13: 9781447104223
DOWNLOAD EBOOKDownload or read book Data Mining and Knowledge Discovery for Process Monitoring and Control written by Xue Z Wang and published by . This book was released on 1999-10-15 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author: Xue Z. Wang
Publisher: Springer Science & Business Media
Published: 2012-12-06
Total Pages: 263
ISBN-13: 1447104218
DOWNLOAD EBOOKModern 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.
Download or read book Data Mining and Knowledge Discovery for Process Monitoring and Control written by Xue Z. Wang and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 263 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Author:
Publisher: BoD – Books on Demand
Published: 2022-03-30
Total Pages: 226
ISBN-13: 1839692669
DOWNLOAD EBOOKThe 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.
Download or read book Data Mining written by and published by BoD – Books on Demand. This book was released on 2022-03-30 with total page 226 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Author: Andrzej Kraslawski
Publisher: Elsevier
Published: 2003-05-07
Total Pages: 1174
ISBN-13: 9780080529448
DOWNLOAD EBOOKThis 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.
Download or read book European Symposium on Computer Aided Process Engineering - 13 written by Andrzej Kraslawski and published by Elsevier. This book was released on 2003-05-07 with total page 1174 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Author: Usman, Muhammad
Publisher: IGI Global
Published: 2018-01-26
Total Pages: 177
ISBN-13: 1522550305
DOWNLOAD EBOOKData 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.
Download or read book Predictive Analysis on Large Data for Actionable Knowledge: Emerging Research and Opportunities written by Usman, Muhammad and published by IGI Global. This book was released on 2018-01-26 with total page 177 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Author: Norio Baba
Publisher: IOS Press
Published: 2001
Total Pages: 860
ISBN-13: 9781586031923
DOWNLOAD EBOOKThe 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.
Download or read book Knowledge-based Intelligent Information Engineering Systems & Allied Technologies written by Norio Baba and published by IOS Press. This book was released on 2001 with total page 860 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Author: János Abonyi
Publisher: Springer Science & Business Media
Published: 2007-08-10
Total Pages: 317
ISBN-13: 376437988X
DOWNLOAD EBOOKThe 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.
Download or read book Cluster Analysis for Data Mining and System Identification written by János Abonyi and published by Springer Science & Business Media. This book was released on 2007-08-10 with total page 317 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Author: Cengiz Kahraman
Publisher: Springer
Published: 2015-10-31
Total Pages: 466
ISBN-13: 331924499X
DOWNLOAD EBOOKThis 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.
Download or read book Intelligent Decision Making in Quality Management written by Cengiz Kahraman and published by Springer. This book was released on 2015-10-31 with total page 466 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Author: Evan L. Russell
Publisher: Springer Science & Business Media
Published: 2012-12-06
Total Pages: 193
ISBN-13: 1447104099
DOWNLOAD EBOOKEarly 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.
Download or read book Data-driven Methods for Fault Detection and Diagnosis in Chemical Processes written by Evan L. Russell and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 193 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Author: Ville Kolehmainen
Publisher: Springer
Published: 2009-09-30
Total Pages: 630
ISBN-13: 3642049214
DOWNLOAD EBOOKThis 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.
Download or read book Adaptive and Natural Computing Algorithms written by Ville Kolehmainen and published by Springer. This book was released on 2009-09-30 with total page 630 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
