الصفحة 1
الصفحة 1
Uncertainty Theory
Uncertainty theory is a branch of mathematics based on normality, monotonicity, self-duality, and countable subadditivity axioms. The goal of uncertainty theory is to study the behavior of uncertain phenomena such as fuzziness and randomness. The main topics include probability theory, credibility theory, and chance theory. For this new edition the entire text has been totally rewritten. More importantly, the chapters on chance theory and uncertainty theory are completely new. This book provides a self-contained, comprehensive and up-to-date presentation of uncertainty theory. The purpose is to equip the readers with an axiomatic approach to deal with uncertainty. Mathematicians, researchers, engineers, designers, and students in the field of mathematics, information science, operations research, industrial engineering, computer science, artificial intelligence, and management science will find this work a stimulating and useful reference.
Transactions on Rough Sets V
Volume V of the Transactions on Rough Sets (TRS) is dedicated to the monu-mental life and work of Zdzis law Pawlak1. During the past 35 years, This volume continues the traditionbegun with earlier volumes of the TRS series and introduces a number of newadvances in the foundations and application of rough sets. These advances haveprofound implications in a number of research areas such as adaptive learning,approximate reasoning and belief systems, approximation spaces, Boolean rea-soning, classification methods, classifiers, concept analysis, data mining, decisionlogic, decision rule importance measures, digital image processing, recognitionof emotionally-charged gestures in animations, flow graphs, Kansei engineering,movie sound track restoration, multicriteria decision analysis, relational informa-tion systems, rough-fuzzy sets, rough measures, signal processing, variable pre-cision rough set model, and video retrieval.
Transactions on Rough Sets III
The LNCS journal Transactions on Rough Sets is devoted to the entire spectrum of rough sets related issues, from logical and mathematical foundations, through all aspects of rough set theory and its applications, such as data mining, knowledge discovery, and intelligent information processing, to relations between rough sets and other approaches to uncertainty, vagueness, and incompleteness, such as fuzzy sets and theory of evidence. This third volume of the Transactions on Rough Sets presents 11 revised papers that have been through a careful peer reviewing process by the journal's Editorial Board. The research monograph "Time Complexity of Decision Trees" by Mikhail Ju. Moshkov is presented in the section on dissertation and monographs. Among the regular papers the one by Zdzislaw Pawlak entitled "Flow Graphs and Data Mining" deserves a special mention.
Transactions on Rough Sets II : Rough Sets and Fuzzy Sets
The LNCS journal Transactions on Rough Sets is devoted to the entire spectrum of rough sets related issues, starting from logical and mathematical foundations, through all aspects of rough set theory and its applications, such as data mining, knowledge discovery, and intelligent information processing, to relations between rough sets and other approaches to uncertainty, vagueness and incompleteness, such as fuzzy sets and theory of evidence. This second volume of the Transactions on Rough Sets presents 17 thoroughly reviewed revised papers devoted to rough set theory, fuzzy set theory; these papers highlight important aspects of these theories, their interrelation and application in various fields.
Transactions on Computational Science II
Transactions on Computational Science II is devoted to the subject of denotational mathematics for computational intelligence. Denotational mathematics, as a counterpart of conventional analytic mathematics, is a category of expressive mathematical structures that deals with high-level mathematical entities beyond numbers and sets, such as abstract objects, complex relations, behavioral information, concepts, knowledge, processes, granules, and systems. This volume includes 12 papers covering the following four important areas: foundations and applications of denotational mathematics; rough and fuzzy set theories; granular computing; and knowledge and information modeling.
Theoretical Advances and Applications of Fuzzy Logic and Soft Computing
This book comprises a selection of papers from the IFSA 2007 World Congress on theoretical advances and applications of fuzzy logic and soft computing. These papers were selected from over 400 submissions and constitute an important contribution to the theory and applications of fuzzy logic and soft computing methodologies. Soft Computing consists of several computing paradigms, including fuzzy logic, neural networks, genetic algorithms, and other techniques, which can be used to produce powerful intelligent systems for solving real-world problems. Applications range from pattern recognition to intelligent control and sow the advantages of using soft computing theory and methods. The papers of IFSA 2007 also make a contribution to this goal.
The Puzzle of Granular Computing
The ultimate goal of this book is to bring the fundamental issues of information granularity, inference tools and problem solving procedures into a coherent, unified, and fully operational framework. The objective is to offer the reader a comprehensive, self-contained, and uniform exposure to the subject.The strategy is to isolate some fundamental bricks of Computational Intelligence in terms of key problems and methods, and discuss their implementation and underlying rationale within a well structured and rigorous conceptual framework as well as carefully related to various application facets. All in all, the main approach advocated in the mono+I241graph consists of a sequence of steps offering solid conceptual fundamentals, presenting a carefully selected collection of design methodologies, discussing a wealth of development guidelines, and exemplifying them with a pertinent, accurately selected illustrative material.
The Fuzzification of Systems : The Genesis of Fuzzy Set Theory and its Initial Applications - Developments up to the 1970s
In 1965 Lotfi Zadeh, a professor of electrical engineering at the University of California in Berkeley, published the first of his papers on his new Fuzzy Set Theory. Since the 1980s this mathematical theory of "unsharp amounts" has been applied in many different fields with great success. The word "fuzzy" has also become very well-known among non-scientists thanks to extensive advertising campaigns for fuzzy-controlled household appliances and to their prominent presence in the media, first in Japan and then in other countries. On the other hand, the story of how Fuzzy Set Theory and its earliest applications originated remains largely unknown. In this book, the history of Fuzzy Set Theory and the ways it was first used are incorporated into the history of 20th century science and technology. Influences from philosophy, system theory and cybernetics stemming from the earliest part of the 20th century are considered along
Simulating Fuzzy Systems
Simulating Fuzzy Systems demonstrates how many systems naturally become fuzzy systems and shows how regular (crisp) simulation can be used to estimate the alpha-cuts of the fuzzy numbers used to analyze the behavior of the fuzzy system. This monograph presents a concise introduction to fuzzy sets, fuzzy logic, fuzzy estimation, fuzzy probabilities, fuzzy systems theory and fuzzy computation. It also presents a wide selection of simulation applications ranging from emergency rooms to machine shops to project scheduling showing the varieties of fuzzy systems.
Simulating Continuous Fuzzy Systems
The authors use crisp continuous simulation to estimate the trajectories of the support and core of these fuzzy numbers in a variety of twenty applications of fuzzy dynamical systems. The applications range from Bungee jumping to the AIDS epidemic to dynamical models in economics. This book is the companion text to "Simulating Fuzzy Systems" (Springer 2005) which investigated discrete fuzzy systems through crisp discrete simulation.
Rough sets, fuzzy sets, data mining, and granular computing ; Vol. 3642 ; 10th International conference, RSFDGrC 2005, Regina, Canada, August 31 - September 2, 2005, Proceedings, Part II
The main idea is based on indiscernibility relations that describe indistinguishability of objects. Concepts are represented by - proximations. In applications, rough set methodology focuses on approximate representation of knowledge derivable from data. It leads to signifcant results in many areas such as , industry, multimedia, and medicine. The RSFDGrC conferences put an emphasis on connections between rough sets and fuzzy sets, granularcomputing, and knowledge discoveryand data m- ing, both at the level of theoretical foundations and real-life applications.
Rough sets, fuzzy sets, data mining, and granular computing ; Vol. 3641 ; 10th International conference, RSFDGrC 2005, Regina, Canada, August 31 - September 3, 2005, Proceedings, Part I
The main idea is based on indiscernibility relations that describe indistinguishability of objects. Concepts are represented by - proximations. In applications, rough set methodology focuses on approximate representation of knowledge derivable from data. It leads to signifcant results in many areas such as industry, multimedia, and medicine. The RSFDGrC conferences put an emphasis on connections between rough sets and fuzzy sets, granularcomputing, and knowledge discoveryand data m- ing, both at the level of theoretical foundations and real-life applications.
Rough Sets, Fuzzy Sets, Data Mining and Granular Computing ; 11th International Conference, RSFDGrC 2007, Toronto, Canada, May 14-16, 2007
This volume contains the papers selected for presentation at the 11th Int- national Conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing (RSFDGrC 2007), a part of the Joint Rough Set Symposium (JRS 2007) organized by Infobright Inc. and York University. JRS 2007 was held for the ?rst time during May 14–16, 2007 in MaRS Discovery District, Toronto, Canada.
Rough Sets and Knowledge Technology ; 2nd International Conference, RSKT 2007, Toronto, Canada, May 14-16, 2007, Proceedings
Constitutes proceedings of the Second International Conference on Rough Sets and Knowledge Technology, RSKT 2007, held in Toronto, Canada in May 2007 in conjunction with the 11th International Conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing, RSFDGrC 2007, both as part of the Joint Rough Set Symposium, JRS 2007.
Rough sets and intelligent systems paradigms ; International Conference, RSEISP 2007, Warsaw, Poland, June 28-30, 2007, Proceedings
This book constitutes the refereed proceedings of the International Conference on Rough Sets and Emerging Intelligent Systems Paradigms, held in Warsaw, Poland in June 2007. Seventy-three full papers are presented, together with two keynote lectures and eleven invited papers.
Rough - Granular Computing in Knowledge Discovery and Data Mining
This book covers methods based on a combination of granular computing, rough sets, and knowledge discovery in data mining (KDD). The discussion of KDD foundations based on the rough set approach and granular computing feature illustrative applications.
Regionalization of Watersheds : An Approach Based on Cluster Analysis
Clustering techniques are used to identify group(s) of watersheds which have similar flood characteristics. This book is a comprehensive reference on how to use these techniques for RFFA and is the first of its kind. It provides a detailed account of several recently developed clustering techniques, including those based on fuzzy set theory and artificial neural networks. It also documents research findings on application of clustering techniques to RFFA that remain scattered in various hydrology and water resources journals.
Preferences and Similarities
The fields of similarity and preference are still broadening due to the exploration of new fields of application. This is caused by the strong impact of vagueness, imprecision, uncertainty and dominance on human and agent information, communication, planning, decision, action, and control as well as by the technical progress of the information technology itself. The topics treated in this book are of interest to computer scientists, statisticians, operations researchers, experts in AI, cognitive psychologists and economists.
Monte Carlo Methods in Fuzzy Optimization
This book is a concise and readable introduction to Monte Carlo methods to find good approximate solutions to fuzzy optimization problems. Various basic applications and illustrative examples are presented in an understandable way. The aim of the book is to convince the reader that Monte Carlo methods can be useful in generating approximate solutions to fuzzy optimization problems.
Modeling of metal forming and machining processes : By finite element and soft computing methods
The physics of metal forming and metal removing is normally expressed using non-linear partial differential equations which can be solved using the finite element method (FEM). However, when the process parameters are uncertain and/or the physics of the process is not well understood, soft computing techniques can be used with FEM or alone to model the process.
