الصفحة 1
الصفحة 1
Uncertainty Forecasting in Engineering
Deals with uncertainty forecasting based on a fuzzy time series approach, including fuzzy random processes and artificial neural networks. A consideration of data and measurement uncertainty enhances forecasting in a wide range of applications, particularly in the fields of engineering, environmental science and civil engineering.Uncertain data are described by means of a new incremental fuzzy representation which permits a complete and accurate estimation of uncertainty.
Mathematics of Uncertainty : Ideas, Methods, Application Problems
Mathematics of Uncertainty" provides the basic ideas and foundations of uncertainty, covering the fields of mathematics in which uncertainty, variability, imprecision and fuzziness of data are of importance. This introductory book describes the basic ideas of the mathematical fields of uncertainty from simple interpolation to wavelets, from error propagation to fuzzy sets and neural networks. The book presents the treatment of problems of interpolation and approximation, as well as observation fuzziness which can essentially influence the preciseness and reliability of statements on functional relationships.
Fuzzy database modeling with XML
Fuzzy Database Modeling with XML aims to provide a single record of current research and practical applications in the fuzzy databases. This volume is the outgrowth of research the author has conducted in recent years. Fuzzy Database Modeling with XML introduces state of the art information to the database research, while at the same time serving the information technology professional faced with a non-traditional application that defeats conventional approaches. The research on fuzzy conceptual models and fuzzy object-oriented databases is receiving increasing attention, in addition to fuzzy relational database models. With rapid advances in network and internet techniques as well, the databases have been applied under the environment of distributed information systems. It is essential in this case to integrate multiple fuzzy database systems. Since databases are commonly employed to store and manipulate XML data, additional requirements are necessary to model fuzzy information with XML. Second, this book maps fuzzy XML model to the fuzzy databases. Very few efforts at investigating these issues have thus far occurred.
Fuzzy Database Modeling of Imprecise and Uncertain Engineering Information
This book presents recent advances for imprecise and uncertain engineering information from the point of view of fuzzy database modeling. The topics include fuzzy conceptual data modeling of engineering information, conversion of the fuzzy conceptual models, and database implementation of the fuzzy conceptual data models. Some major data and database models for engineering information modeling are investigated. The main novel aspect of this book is that the book focuses on imprecise and uncertain industrial information modeling viewed from databases and fuzzy database technologies viewed from industrial applications. This may be useful for people involved in theory research, design implementation, and application development of intelligent engineering databases.
Fundamentals of statistics with fuzzy data
This research monograph presents basic foundational aspects for a theory of statistics with fuzzy data, together with a set of practical applications. Fuzzy data are modeled as observations from random fuzzy sets. Theories of fuzzy logic and of random closed sets are used as basic ingredients in building statistical concepts and procedures in the context of imprecise data, including coarse data analysis. The monograph also aims at motivating statisticians to look at fuzzy statistics to enlarge the domain of applicability of statistics in general.
From Data and Information Analysis to Knowledge Engineering ; Proceedings of the 29th Annual Conference of the Gesellschaft für Klassifikation e.V., University of Magdeburg, March 9-11, 2005
The volume contains revised versions of selected papers presented during the 29th Annual Conference of the Gesellschaft für Klassifikation (GfKl), the German Classification Society, held at the Otto-von-Guericke-University of Magdeburg, Germany, in March 2005. In addition to papers on the traditional subjects Classification, Clustering, and Data Analysis, there are many papers on a wide range of topics with a strong relation to Computer Science. Examples are Text Mining, Web Mining, Fuzzy Data Analysis, IT Security, Adaptivity and Personalization, and Visualization. Application-oriented topics include Economics, Marketing, Banking and Finance, Medicine, Bioinformatics, Biostatistics, and Music Analysis.
Computational intelligence : Principles, techniques and applications
The book Computational Intelligence: Principles, Techniques and Applications presents both theories and applications of Computational Intelligence in a clear, precise and highly comprehensive style. The textbook addresses the fundamental aspects of Fuzzy Sets and Logic, Neural Networks, Evolutionary Computing and Belief Networks. The application areas include Fuzzy Databases, Fuzzy Control, Image Understanding, Expert Systems, Object Recognition, Criminal Investigation, Telecommunication Networks and Intelligent Robots. The book contains many numerical examples and homework problems with sufficient hints so that the students can solve them on their own. Emerging areas of Computational Intelligence such as artificial life, particle swarm optimization, artificial immune systems, fuzzy chaos theory, rough sets and granular computing have also been addressed with examples in this book. The book ends with a discussion on a number of open- ended research problems in Computational Intelligence. Graduate students interested to pursue their research in this subject will greatly be benefited with these problems.
