Frank Klawonn – författare

Provides a timely and important introduction to fuzzy cluster analysis, its methods and areas of application, systematically describing different fuzzy clustering techniques so the user may choose methods appropriate for his problem. It provides a very thorough overview of the subject and covers classification, image recognition, data analysis and rule generation. The application examples are highly relevant and illustrative, and the use of the techniques are justified and well thought-out. Features include: * Sections on inducing fuzzy if-then rules by fuzzy clustering and non-alternating optimization fuzzy clustering algorithms * Discussion of solid fuzzy clustering techniques like the fuzzy c-means, the Gustafson-Kessel and the Gath-and-Geva algorithm for classification problems * Focus on linear and shell clustering techniques used for detecting contours in image analysis * Accompanying software and data sets pertaining to the examples presented, enabling the reader to learn through experimentation * Examination of the difficulties involved in evaluating the results of fuzzy cluster analysis and of determining the number of clusters with analysis of global and local validity measures This is one of the most comprehensive books on fuzzy clustering and will be welcomed by computer scientists, engineers and mathematicians in industry and research who are concerned with different methods, data analysis, pattern recognition or image processing. It will also give graduate students in computer science, mathematics or statistics a valuable overview.

Each passing year bears witness to the development of ever more powerful computers, increasingly fast and cheap storage media, and even higher bandwidth data connections. This makes it easy to believe that we can now – at least in principle – solve any problem we are faced with so long as we only have enough data.Yet this is not the case. Although large databases allow us to retrieve many different single pieces of information and to compute simple aggregations, general patterns and regularities often go undetected. Furthermore, it is exactly these patterns, regularities and trends that are often most valuable.To avoid the danger of “drowning in information, but starving for knowledge” the branch of research known as data analysis has emerged, and a considerable number of methods and software tools have been developed. However, it is not these tools alone but the intelligent application of human intuition in combination with computational power, of sound background knowledge with computer-aided modeling, and of critical reflection with convenient automatic model construction, that results in successful intelligent data analysis projects. Guide to Intelligent Data Analysis provides a hands-on instructional approach to many basic data analysis techniques, and explains how these are used to solve data analysis problems.Topics and features: guides the reader through the process of data analysis, following the interdependent steps of project understanding, data understanding, data preparation, modeling, and deployment and monitoring; equips the reader with the necessary information in order to obtain hands-on experience of the topics under discussion; provides a review of the basics of classical statistics that support and justify many data analysis methods, and a glossary of statistical terms; includes numerous examples using R and KNIME, together with appendices introducing the open source software; integrates illustrations and case-study-style examplesto support pedagogical exposition.This practical and systematic textbook/reference for graduate and advanced undergraduate students is also essential reading for all professionals who face data analysis problems. Moreover, it is a book to be used following one’s exploration of it.Dr. Michael R. Berthold is Nycomed-Professor of Bioinformatics and Information Mining at the University of Konstanz, Germany. Dr. Christian Borgelt is Principal Researcher at the Intelligent Data Analysis and Graphical Models Research Unit of the European Centre for Soft Computing, Spain. Dr. Frank Höppner is Professor of Information Systems at Ostfalia University of Applied Sciences, Germany. Dr. Frank Klawonn is a Professor in the Department of Computer Science and Head of the Data Analysis and Pattern Recognition Laboratory at Ostfalia University of Applied Sciences, Germany. He is also Head of the Bioinformatics and Statistics group at the Helmholtz Centre for Infection Research, Braunschweig, Germany.

This clearly-structured, classroom-tested textbook/reference presents a methodical introduction to the field of CI. Providing an authoritative insight into all that is necessary for the successful application of CI methods, the book describes fundamental concepts and their practical implementations, and explains the theoretical background underpinning proposed solutions to common problems. Only a basic knowledge of mathematics is required. Features: provides electronic supplementary material at an associated website, including module descriptions, lecture slides, exercises with solutions, and software tools; contains numerous examples and definitions throughout the text; presents self-contained discussions on artificial neural networks, evolutionary algorithms, fuzzy systems and Bayesian networks; covers the latest approaches, including ant colony optimization and probabilistic graphical models; written by a team of highly-regarded experts in CI, with extensive experience in both academia and industry.

Major updates on techniques and subject coverage (including deep learning) are included. Topics and features: guides the reader through the process of data science, following the interdependent steps of project understanding, data understanding, data blending and transformation, modeling, as well as deployment and monitoring;

Major updates on techniques and subject coverage (including deep learning) are included. Topics and features: guides the reader through the process of data science, following the interdependent steps of project understanding, data understanding, data blending and transformation, modeling, as well as deployment and monitoring;

A basic understanding of the key techniques in computer graphics can open the door to this exciting field and its many applications, including for video games and for augmented and virtual reality.This easy-to-follow textbook and reference introduces the fundamental concepts of computer graphics, integrating both technical background and theory with practical examples and applications throughout. Thoroughly revised and updated, this new edition continues to present a user-friendly approach to creating images and animations, complementing the expanded coverage of topics with usage of example programs and exercises.Topics and features:Contains pedagogical tools, including easy-to-understand example programs and end-of-chapter exercisesPresents a practical guide to basic computer graphics programming using the Open Graphics Library (OpenGL) and the widely used Java programming languageIncludes new and expanded content on the OpenGL graphics pipelines, shader programming, drawing basic objects using the OpenGL, three-dimensional modelling, quaternions, rasterisation, antialiasing and moreSupplies complete Java project examples as supplementary materialThis reader-friendly textbook is an essential tool for second-year undergraduate students and above, providing clear and concise explanations of the basic concepts of computer graphics. It will enable readers to immediately implement these concepts using the OpenGL and Java (with only elementary knowledge of the programming language).Prof. Dr.-Ing. Karsten Lehn works at the Faculty of Information Technology at Fachhochschule Dortmund, University of Applied Sciences and Arts. Prof. Dr. Merijam Gotzes is teaching at Hamm-Lippstadt University of Applied Sciences. Prof. Dr. Frank Klawonn is head of the Data Analysis and Pattern Recognition Laboratory at the Ostfalia University of Applied Sciences and heads the Biostatistics Research Group at the Helmholtz Centre for Infection Research.

This book constitutes the refereed proceedings of the 17 International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2016, held in Yangzhou, China, in October 2016.

Dieses Buch ist das Standardwerk zu einem neuen Bereich der angewandten Fuzzy-Technologie, der Fuzzy-Clusteranalyse. Diese beinhaltet Verfahren der Mustererkennung zur Gruppierung und Strukturierung von Daten. Dabei werden im Gegensatz zu klassischen Clustering-Techniken die Daten nicht eindeutig zu Klassen zugeordnet, sondern Zugehorigkeitsgrade bestimmt, so dass die Fuzzy-Verfahren robust gegenuber gestorten oder verrauschten Daten sind und fliessende Klassenubergange handhaben konnen. Dieses Werk gibt eine methodische Einfuhrung in die zahlreichen Fuzzy-Clustering-Algorithmen mit ihren Anwendungen in den Bereichen Datenanalyse, Erzeugung von Regeln fur Fuzzy-Regler, Klassifikations- und Approximationsprobleme sowie eine ausfuhrliche Darstellung des Shell-Clustering zur Erkennung von geometrischen Konturen in Bildern.

This carefully edited book covers a wide range of application areas of soft computing such as optimization, data analysis and data mining, fault diagnosis, control as well as traffic and transportation systems. It contains 25 revised contributions from the 8th Online World Conferences on Soft Computing (WSC8). The collected papers show how the major soft computing techniques, fuzzy systems, neural networks and evolutionary algorithms and especially hybrid systems combining methods from these fields, lead to successful industrial applications. The reader will find an interesting, inspiring and wide variety of soft computing techniques and applications in this book.

“Fuzzy Control - the revolutionary computer technology that is changing our world” - these and other headlines could be read when in the early 90’s news from Japan came over telling us about the success of fuzzy controllers. The idea which was put into practice had been suggested by Lot? A. Zadeh in Berkeley in 1965. It had been developed and tested in some practical - plications, especially in Europe. In Japan fuzzy control was celebrated as a technology re?ecting the Japanese way of thinking by its unsharpness and - plicitoverlappingofseveralstatements. Anewtechnologyboomwaspredicted for Japan which would make Europe lose ground. Consequently, this news created unrest. Research projects were initiated and development departments were engaged to translate fuzzy control into products. Adversaries and supporters hurried up to inform themselves and intensely discussed whether the “conventional” or the fuzzy control were the better alternative. Finally, the excitement cooled down since in recent years fuzzy control was analyzed fromthe classical pointofview. Thus,amoreobjective evaluation of its strong and weak points was possible. Furthermore, it was shown how fuzzy systems could be put to use in the steering level which is the level above the control loop, especially in interaction with other methods of soft computing and arti?cial intelligence. Based on these fundamentals, the aim of this book is to support the convenient use of fuzzy controllers and fuzzy systems in the branch of control engineering and automation systems.

Nachdem die ersten Fuzzy-Regler Anfang der siebziger Jahre entwickelt und in der Praxis erprobt wurden, hat das Gebiet der Fuzzy-Regelung in den vergangenen Jahrzehnten einen gewaltigen Fortschritt erfahren. Die zugrunde liegenden mathematischen und technischen Konzepte sind umfassend analysiert worden, und mittlerweile werden Fuzzy-Regler in vielen industriellen Anwendungen routinemäßig eingesetzt. Das Ziel dieses Buches ist eine kritische Bestandsaufnahme der Fuzzy-Regler aus Sicht der klassischen Regelungstechnik. Der Schwerpunkt dieses Buches liegt in der Darstellung von Themen, die für den Anwender von besonderem Interesse sind. Hierzu zählen insbesondere die (Selbst-) Einstellung, Optimierung und Stabilitätsanalyse von Fuzzy-Reglern. Ausgehend von einer detaillierten Einführung in die Gebiete Fuzzy-Systeme und Regelungstechnik wird der Leser systematisch an aktuelle Forschungsergebnisse herangeführt.

“Fuzzy Control - the revolutionary computer technology that is changing our world” - these and other headlines could be read when in the early 90’s news from Japan came over telling us about the success of fuzzy controllers. The idea which was put into practice had been suggested by Lot? A. Zadeh in Berkeley in 1965. It had been developed and tested in some practical - plications, especially in Europe. In Japan fuzzy control was celebrated as a technology re?ecting the Japanese way of thinking by its unsharpness and - plicitoverlappingofseveralstatements. Anewtechnologyboomwaspredicted for Japan which would make Europe lose ground. Consequently, this news created unrest. Research projects were initiated and development departments were engaged to translate fuzzy control into products. Adversaries and supporters hurried up to inform themselves and intensely discussed whether the “conventional” or the fuzzy control were the better alternative. Finally, the excitement cooled down since in recent years fuzzy control was analyzed fromthe classical pointofview. Thus,amoreobjective evaluation of its strong and weak points was possible. Furthermore, it was shown how fuzzy systems could be put to use in the steering level which is the level above the control loop, especially in interaction with other methods of soft computing and arti?cial intelligence. Based on these fundamentals, the aim of this book is to support the convenient use of fuzzy controllers and fuzzy systems in the branch of control engineering and automation systems.

This book constitutes the refereed proceedings of the 11th International Conference on Intelligent Data Analysis, IDA 2012, held in Helsinki, Finland, in October 2012. The 32 revised full papers presented together with 3 invited papers were carefully reviewed and selected from 88 submissions. All current aspects of intelligent data analysis are addressed, including intelligent support for modeling and analyzing data from complex, dynamical systems. The papers focus on novel applications of IDA techniques to, e.g., networked digital information systems; novel modes of data acquisition and the associated issues; robustness and scalability issues of intelligent data analysis techniques; and visualization and dissemination results.

This book constitutes the refereed proceedings of the Second International Conference on Health Information Science, HIS 2013, held in London, UK, in March 2013. The 20 full papers presented together with 3 short papers, 3 demo papers and one poster in this volume were carefully reviewed and selected from numerous submissions. The papers cover all aspects of health information sciences and systems that support the health information management and health service delivery. The scope of the conference includes 1) medical/health/biomedicine information resources, such as patient medical records, devices and equipments, software and tools to capture, store, retrieve, process, analyse, and optimize the use of information in the health domain, 2) data management, data mining, and knowledge discovery, all of which play a key role in the decision making, management of public health, examination of standards, privacy and security issues, and 3) development of new architectures and applications for health information systems.

This book constitutes the refereed proceedings of the 14th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2013, held in Hefei, China, in October 2013. The 76 revised full papers presented were carefully reviewed and selected from more than 130 submissions. These papers provided a valuable collection of latest research outcomes in data engineering and automated learning, from methodologies, frameworks and techniques to applications. In addition to various topics such as evolutionary algorithms, neural networks, probabilistic modelling, swarm intelligent, multi-objective optimisation, and practical applications in regression, classification, clustering, biological data processing, text processing, video analysis, including a number of special sessions on emerging topics such as adaptation and learning multi-agent systems, big data, swarm intelligence and data mining, and combining learning and optimisation in intelligent data engineering.

Die Autoren behandeln umfassend zentrale Themen der Informatik von Künstlichen Neuronalen Netzen, über Evolutionäre Algorithmen bis hin zu Fuzzy-Systemen und Bayes-Netzen.