Applied Research in Uncertainty Modeling and Analysis

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Bilal Ayyub
Springer Science & Business Media, Dec 29, 2007 - Business & Economics - 545 pages
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The application areas of uncertainty are numerous and diverse, including all fields of engineering, computer science, systems control and finance. Determining appropriate ways and methods of dealing with uncertainty has been a constant challenge. The theme for this book is better understanding and the application of uncertainty theories. This book, with invited chapters, deals with the uncertainty phenomena in diverse fields. The book is an outgrowth of the Fourth International Symposium on Uncertainty Modeling and Analysis (ISUMA), which was held at the center of Adult Education, College Park, Maryland, in September 2003. All of the chapters have been carefully edited, following a review process in which the editorial committee scrutinized each chapter. The contents of the book are reported in twenty-three chapters, covering more than . . ... pages. This book is divided into six main sections. Part I (Chapters 1-4) presents the philosophical and theoretical foundation of uncertainty, new computational directions in neural networks, and some theoretical foundation of fuzzy systems. Part I1 (Chapters 5-8) reports on biomedical and chemical engineering applications. The sections looks at noise reduction techniques using hidden Markov models, evaluation of biomedical signals using neural networks, and changes in medical image detection using Markov Random Field and Mean Field theory. One of the chapters reports on optimization in chemical engineering processes.
 

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Contents

PHILOSOPHICAL AND THEORETICAL BASES FOR ANALYZING AND MODELING UNCERTAINTY AND IGNORANCE
1
A SELFORGANIZING NEURAL NETWORK BY DYNAMIC AND SPATIAL CHANGING WEIGHTS
19
SIMULATION OF FUZZY SYSTEMS I
31
SIMULATION OF FUZZY SYSTEMS II
61
EVENTRELATED POTENTIAL NOISE REDUCTION USING THE HIDDEN MARKOV TREE MODEL
91
CHANGE DETECTION IN IMAGE SEQUENCE BASED ON MARKOV RANDOM FIELD AND MEAN FIELD THEORY
115
ANALYSIS OF MULTICHANNEL SUBDURAL EEG BY RECURRENT NEURAL NETWORKS
138
MULTICRITERIA OPTIMIZATION UNDER PARAMETRIC UNCERTAINTY
161
STUDY OF TRANSPORTATION AND UNCERTAINTY
303
MULTI AGENT SYSTEMS APPROACH TO PARKING FACILITIES MANAGEMENT
320
MODELING TRANSPORTATION CHOICE THROUGH UTILITYBASED MULTILAYER FEEDFORWARD NETWORKS
341
HETEROGENEITY IN COMMUTER DEPARTURE TIME DECISION A PROSPECT THEORETIC APPROACH
369
IMPORTANCE OF FUZZY SETS DEFINITIONS FOR FUZZY SIGNAL CONTROLLERS
399
RELIABILITY EVALUATION OF REALISTIC STRUCTURES USING FEM
417
SIMULATION IN RISKBASED CODIFIED ENGINEERING DESIGN
443
SYSTEM IDENTIFICATION AT LOCAL LEVEL UNDER UNCERTAINTY
461

DESIGN OF NEURAL NETWORKS FOR PAVEMENT RUTTING
192
NEURAL NETWORKS FOR RESIDENTIAL INFRASTRUCTURE MANAGEMENT
215
EVACUATION SIMULATION IN UNDERGROUND MALL BY ARTIFICIAL LIFE TECHNOLOGY
249
EPISTEMIC UNCERTAINTY AND THE MANAGEMENT OF HIGH RISK EXPOSURES
266
EXPERIMENT WITH A HIERARCHICAL TEXT CATEGORIZATION METHOD ON WIPO PATENT COLLECTIONS
283
UNCERTAINTY MODELING OF CHLORIDE CONTAMINATION AND CORROSION OF CONCRETE BRIDGES
491
REDUNDANCY ANALYSIS OF STRUCTURAL SYSTEMS
512
INDEX
533
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