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This book combines material from our previous books FP (Fuzzy Probabilities: New Approach and Applications,Physica-Verlag, 2003) and FS (Fuzzy Statistics, Springer, 2004), plus has about one third new results.
A broad introduction to the topic of aggregation functions is to be found in this book. Particular attention is paid to identification and construction of aggregation functions from application specific requirements and empirical data.
This carefully edited book presents an up-to-date state of current research in the use of fuzzy sets and their extensions. It pays particular attention to foundation issues and to their application to four important areas where fuzzy sets are seen to be an important tool for modeling and solving problems.
This book explores the intersection of fuzzy mathematics and the spatial modeling of preferences in political science.
This book presents several important papers presented by some of the well-known scientists from all over the globe. The main techniques of soft computing presented include ant-colony optimization, artificial immune systems, artificial neural networks, Bayesian models.
This text offers the general scientific community the epistemic framework of fuzzy paradigm and the rationality it induces for approximate reasoning. It also describes the role fuzzy rationality plays in our information-knowledge enterprise.
This monograph describes new methods for intelligent pattern recognition using soft computing techniques including neural networks, fuzzy logic, and genetic algorithms.
Presently, general-purpose optimization techniques such as Simulated Annealing, and Genetic Algorithms, have become standard optimization techniques.
Fuzzy set approaches are suitable to use when the modeling of human knowledge is necessary and when human evaluations are needed. Fuzzy set theory is now - plied to problems in engineering, business, medical and related health sciences, and the natural sciences.
Soft computing techniques are widely used in most businesses. This book consists of several important papers on a broad range of applications of soft computing techniques for the business field.
From the inception of the PERT method in the 1950's, it was acknowledged that data concerning activity duration times is generally not perfectly known and the study of stochastic PERT was launched quite early.
Recently many researchers are working on cluster analysis as a main tool for exploratory data analysis and data mining.
Machine learning is currently one of the most rapidly growing areas of research in computer science. symbolic learning, neural networks and genetic algorithms as well as providing a tutorial on learning casual influences.
This book provides a critical discussion of fuzzy controllers from the perspective of classical control theory. The text begins with a detailed introduction to fuzzy systems and control theory, and guides the reader to a thorough understanding of up-to-date research results.
At the beginning of the new millennium, fuzzy logic opens a new challenging perspective in information processing. This perspective emerges out of the ideas of the founder of fuzzy logic - Lotfi Zadeh, to develop 'soft' tools for direct computing with human perceptions.
From the basic motor behavior in some exotic robot architectures right through to the planning of complex behaviors or the evolution of robot control structures, the book explores different degrees and definitions of autonomous behavior.
The Web is the nervous system of information society. The articles that comprise lEW address many basic problems ranging from structure analysis of Internet documents and Web dialogue management to intelligent Web agents for extraction of information, and bootstrapping an ontology-based information extraction system.
The last two decades have witnessed an enormous growth with regard to ap plications of information theoretic framework in areas of physical, biological, engineering and even social sciences. Claude Shannon in 1948 laid the foundation of the field of information theory in the context of communication theory.
This volume covers the fields of measurement and information acqulSltlon. Nowadays information acquisition should not only provide more information but also provide it in such a way as to assure effective and efficient processing of this information.
Soft computing has provided sophisticated methodologies for the development of intelligent decision support systems.
This monograph presents the latest advances of fuzzy logic and soft computing in reservoir characterization and modeling. It proposes for the first time that future develoments require perception-based information processing.
This book provides a new grade methodology for intelligent data analysis. This monograph is the only book presently available covering both the theory and application of grade data analysis and therefore aiming both at researchers, students, as well as applied practitioners.
The field of neural information processing has two main objects: investigation into the functioning of biological neural networks and use of artificial neural networks to sol ve real world problems. Hoshino and Zheng simulate a neural network of the auditory cortex to investigate neural basis for encoding and perception of vowel sounds.
Soft computing is playing an increasing role in the study of complex systems in science and engineering. It covers a range of core topics from software engineering that are soft from its very nature: selection of components, software design, software reuse, software cost estimation and software processes.
"Soft Computing and its Applications in Business and Economics," or SC-BE for short, is a work whose importance is hard to exaggerate.
the objects and ends constitute the specific differ ence There is nothing in the intellect that has not already been in the senses, that is, in the sensory organs, that has not already been in sensible things from which are distinguished things not perceptible to the senses.
Gupta The development of cost benefit analysis and the theory of fuzzy decision was divided into two inter-dependent structures of identification and measurement theory on one hand and fuzzy value theory one the other.
Incorporation of a priori knowledge, such as expert knowledge, meta-heuristics and human preferences, as well as domain knowledge acquired during evolu tionary search, into evolutionary algorithms has received increasing interest in the recent years.
In today's increasingly complex and uncertain business environment, financial analysis is yet more critical to business managers who tackle problems of an economic or business nature.
This book presents basic aspects for a theory of statistics with fuzzy data, together with a set of practical applications. The book aims at motivating statisticians to examine fuzzy statistics to enlarge the domain of applicability of statistics in general.
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