Guoqing Chen – författare

This text addresses fundamental issues of fuzzy data modelling, such as fuzzy data representation, fuzzy integrity constraints, fuzzy conceptual modelling, and fuzzy database design. The purpose of introducing fuzzy logic in data modelling is to enhance the classical models such that uncertain and imprecise information can be represented and manipulated. Fuzzy data representation reflects how, where and to what extent fuzziness is incorporated into classical models. Fuzzy integrity constraints are a sort of fuzziness-involved business rules and semantic restrictions that need to be specified and enforced. Fuzzy conceptual modelling describes and treats high-level data concepts and related semantics in a fuzzy context, allowing the model to tolerate imprecision at different degrees. Fuzzy database design provides guidelines for how relation schemes of fuzzy databases should be formed and develops remedies to possible problems of data redundancy and update anomalies.

This volume contains contributions from world-leading experts from both the academic and industrial communities. The first part of the volume consists of invited papers by international authors describing possibilistic logic in decision analysis, fuzzy dynamic programming in optimization, linguistic modifiers for word computation, and theoretical treatments and applications of fuzzy reasoning. The second part is composed of 11 contributions from Chinese authors focusing on some of the key issues in the fields: stable adaptive fuzzy control systems; partial evaluations and fuzzy reasoning; fuzzy wavelet neural networks; analysis and applications of genetic algorithms; partial repeatability; rough set reduction for data enriching; limits of agents in process calculus; medium logic and its evolution; and factor spaces canes. These contributions are not only theoretically sound and well-formulated, but are also coupled with applicability implications and/or implementation treatments. The domains of applications realized or implied are: decision analysis; word computation; databases and knowledge discovery; power systems; control systems; and multi-destinational routing.Furthermore, the articles contain materials that are an outgrowth of recently conducted research in the late 1990s, addressing fundamental and important issues of fuzzy logic and soft computing.

also in: THE KLUWER INTERNATIONAL SERIES ON ASIAN STUDIES IN COMPUTER AND INFORMATION SCIENCE, Volume 2

Fuzzy Logic and Soft Computing contains contributions from world-leading experts from both the academic and industrial communities. The first part of the volume consists of invited papers by international authors describing possibilistic logic in decision analysis, fuzzy dynamic programming in optimization, linguistic modifiers for word computation, and theoretical treatments and applications of fuzzy reasoning. The second part is composed of eleven contributions from Chinese authors focusing on some of the key issues in the fields: stable adaptive fuzzy control systems, partial evaluations and fuzzy reasoning, fuzzy wavelet neural networks, analysis and applications of genetic algorithms, partial repeatability, rough set reduction for data enriching, limits of agents in process calculus, medium logic and its evolution, and factor spaces canes. These contributions are not only theoretically sound and well-formulated, but are also coupled with applicability implications and/or implementation treatments. The domains of applications realized or implied are: decision analysis, word computation, databases and knowledge discovery, power systems, control systems, and multi-destinational routing. Furthermore, the articles contain materials that are an outgrowth of recently conducted research, addressing fundamental and important issues of fuzzy logic and soft computing.

"Intelligent Data Mining – Techniques and Applications" is an organized edited collection of contributed chapters covering basic knowledge for intelligent systems and data mining, applications in economic and management, industrial engineering and other related industrial applications. The main objective of this book is to gather a number of peer-reviewed high quality contributions in the relevant topic areas. The focus is especially on those chapters that provide theoretical/analytical solutions to the problems of real interest in intelligent techniques possibly combined with other traditional tools, for data mining and the corresponding applications to engineers and managers of different industrial sectors. Academic and applied researchers and research students working on data mining can also directly benefit from this book.

"Intelligent Data Mining -- Techniques and Applications" is an organized edited collection of contributed chapters covering basic knowledge for intelligent systems and data mining, applications in economic and management, industrial engineering and other related industrial applications. The main objective of this book is to gather a number of peer-reviewed high quality contributions in the relevant topic areas. The focus is especially on those chapters that provide theoretical/analytical solutions to the problems of real interest in intelligent techniques possibly combined with other traditional tools, for data mining and the corresponding applications to engineers and managers of different industrial sectors. Academic and applied researchers and research students working on data mining can also directly benefit from this book.