Vital information on machine intelligence and pattern recognition is provided by this publication. In particular, the 31 papers discuss the ways in which uncertainty modelling and analysis are becoming an integral part of system definition and modelling in many fields. Contributions are sourced from an international base of researchers, scientists and engineers working on theoretical developments and diversified applications in engineering systems. The book is divided into two main parts. The first, Uncertainty Models and Measures, includes chapters on theoretical studies and developments carried out on uncertainty (including cognitive uncertainty and how it relates to information and intelligence), information, fuzzy logic, expert systems and neural networks. There are also chapters on modelling uncertainty in the reliability assessment of complex systems, linguistic connectives, the principle of maximum buoyancy, uncertain evidence, inductive learning, convex modelling, new uncertainty measures and information and uncertainty.The larger second part, Applications to Engineering Systems, contains application-oriented studies in fields related to civil, electrical, energy and general engineering systems. The papers cover studies on general uncertainty types in structural engineering, bridges, transmission structures, structural reliability, structural identification, system life cycle analysis, control, construction activities, decision analysis, signal detection, risk management, product quality, military command and control, data bases, long-term projections and predictions and assessment of insurance indices.The book conveys the excitement, advances and promises that all these fields offer to our expanding information-based technological society. It also hopes to stimulate the interest of other researchers around the world who are facing the challenge of new theoretical studies and innovative technological changes.
Vital information on machine intelligence and pattern recognition is provided by this publication. In particular, the 31 papers discuss the ways in which uncertainty modelling and analysis are becoming an integral part of system definition and modelling in many fields. Contributions are sourced from an international base of researchers, scientists and engineers working on theoretical developments and diversified applications in engineering systems. The book is divided into two main parts. The first, Uncertainty Models and Measures, includes chapters on theoretical studies and developments carried out on uncertainty (including cognitive uncertainty and how it relates to information and intelligence), information, fuzzy logic, expert systems and neural networks. There are also chapters on modelling uncertainty in the reliability assessment of complex systems, linguistic connectives, the principle of maximum buoyancy, uncertain evidence, inductive learning, convex modelling, new uncertainty measures and information and uncertainty.The larger second part, Applications to Engineering Systems, contains application-oriented studies in fields related to civil, electrical, energy and general engineering systems. The papers cover studies on general uncertainty types in structural engineering, bridges, transmission structures, structural reliability, structural identification, system life cycle analysis, control, construction activities, decision analysis, signal detection, risk management, product quality, military command and control, data bases, long-term projections and predictions and assessment of insurance indices.The book conveys the excitement, advances and promises that all these fields offer to our expanding information-based technological society. It also hopes to stimulate the interest of other researchers around the world who are facing the challenge of new theoretical studies and innovative technological changes.
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Elsevier Science & Technology
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Illustrationen
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978-0-444-81954-3 (9780444819543)
Copyright in bibliographic data is held by Nielsen Book Services Limited or its licensors: all rights reserved.
Schweitzer Klassifikation
Herausgeber*in
University of Maryland, Department of Civil Engineering, College Park, MD, USA
University of Saskatchewan, Intelligent Systems Research Laboratory, Saskatoon, Sask., Canada
Dedication. Foreword. Preface. Table of Contents. List of Contributors. Biographical Information about the Editors. Uncertainty Models and Measures. The many faces of uncertainty (G.J. Klir). Linguistic connectives and second order semantic uncertainty (I.B. Tuerksen). Completing orderings using the principle of maximal buoyancy (R.R. Yager). Maximally uncertain evidence (A. Ramer, C. Padet). Uncertainties in the analysis of large-scale systems (V. Perincherry, S. Kikuchi, Y. Hamamatsu). Inductive learning of membership functions and fuzzy rules (M. Sebag, M. Schoenauer). Coordination and control of nonlinear multivariable systems with parametric and structural uncertainties using a dynamic neural network (D.H. Rao, M.M. Gupta). Possibilistic and necessistic reliability functions: fundamental concepts and theorems to represent non-probabilistic uncertainty in reliability theory (B. Cappelle, E.E. Kerre). A new safety factor based on convex modelling (I. Elishakoff). An order-theoretic approach to the measuring of fuzziness (B. De Baets, E.E. Kerre). Applications to Engineering Systems. The nature of uncertainty in structural engineering (B.M. Ayyub). Uncertainty irrelevance and preferences over ambiguity in expected utility decision making (V.M. Bier). A decision making model under uncertainty applied to managing risk (K. Engemann, H. Miller, R. Yager). Applying fuzzy decision theory to deal with the uncertainty in military command and control process (X.-S. Luo). System life cycle analysis and assessment under uncertainty (O.A. Asbjornsen). Multi-attribute fuzzy control of construction activities (M.H.M. Hassan, B.M. Ayyub). Modelling uncertainty in construction simulation (S.M. AbouRizk, D.W. Halpin, A. Sawhney). Project scheduling of bridge construction by fuzzy PERT (Y. Natsuaki, H. Furuta, K. Muto, H. Ninomiya). Finite element-based structural identification under uncertainty (D. Wang, A. Haldar). Fuzzy optimal seismic control system of buildings - uncertainties in prediction of earthquake input, structural identification and optimization (A. Tani, H. Kawamura). Aesthetic design of bridges by neural network and expert system (K. Yasuda, H. Furuta, H. Yamanishi). Fuzzy expert system for dimensioning superstructures of steel bridges (K. Nukatani, K. Yasuda, L.H. Ichinose, H. Furuta). A method of empirical knowledge acquisition for a serviceability rating system on existing bridges (M. Kushida, T. Tokuyama, A. Miyamoto). Optimum cable tension adjustment based upon fuzzy mathematical programming (H. Furuta, M. Kamei, M. Kaneyoshi, H. Tanaka). Quantification of Bridge Pier Scour uncertainty (P.A. Johnson). Treatment of uncertainty in a fuzzy logic expert system for damage assessment of transmission structures (I. Hathout). Fuzzy modelling for designing product of consumer-perceived quality (H.-P. Kao, D.L. Kimbler, C.-H. Juang, W.C. Bridges). Signal detection models incorporating uncertainty: sensitivity to parameter estimates (J.R. Boston). Uncertainty estimates in scientific models: lessons from trends in physical measurements, population and energy projections (A.I. Shlyakhter). A new earthquake insurance/reinsurance index: its uncertainties and future developments (C.E. Taylor, J. Lemaire, C. Tillman). Tools for assisting the design of fuzzy applications and the retrieval of fuzzy information from (FIRMS) an object oriented fuzzy system (N. Mouaddib, P. Subtil). Contributors Index. Subject Index.
