Ayyub Applied Research in Uncertainty Modeling Analysis

1. Auflage 2004
ISBN: 978-0-387-23550-9
Verlag: Springer
Format: PDF
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, Band 20, 545 Seiten

Reihe: The Kluwer International Series in Intelligent Technologies

Uncertainty has been - concern to engineers, managers, and scientists for many years in engineering and sciences. Uncertainty has for - long time been considered synonymous with random, stochastic, statistic, or probabilistic. Since the early sixties views on uncertainty have become more heterogeneous and more tools that model uncertainty than statistics have been proposed by several engineers and scientists. The tool/ method to model uncertainty in - specific context should really be choices by considering the features of the phenomenon under consideration not independently of what is known about the system and what causes uncertainty. 'Applied Research in Uncertainty Modeling Analysis' concentrates on general aspects of uncertainty, modeling, and methods, and consists of large numbers of examples on engineering and sciences.

Zielgruppe

Engineering, general, Economic Theory/Mathematical Methods, Operation Research/Decision Theory

Autoren/Hrsg.

Ayyub, Bilal

Fachgebiete

• Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Numerische Mathematik
• Technische Wissenschaften Technik Allgemein Mathematik für Ingenieure
• Wirtschaftswissenschaften Betriebswirtschaft Wirtschaftsmathematik und -statistik
• Wirtschaftswissenschaften Volkswirtschaftslehre Volkswirtschaftslehre Allgemein Ökonometrie

Inhaltsverzeichnis

1;LIST OF CONTRIBUTORS;7
2;FOREWORD;10
3;PREFACE;12
4;CONTENTS;14
5;Chapter 1 PHILOSOPHICAL AND THEORETICAL BASES FOR ANALYZING AND MODELING UNCERTAINTY AND IGNORANCE;16
6;Chapter 2 A SELF-ORGANIZING NEURAL NETWORK BY DYNAMIC AND SPATIAL CHANGING WEIGHTS;34
7;Chapter 3 SIMULATION OF FUZZY SYSTEMS I;46
8;Chapter 4 SIMULATION OF FUZZY SYSTEMS II;76
9;Chapter 5 EVENT - RELATED POTENTIAL NOISE REDUCTION USING THE HIDDEN MARKOV TREE MODEL;106
10;Chapter 6 CHANGE DETECTION IN IMAGE SEQUENCE BASED ON MARKOV RANDOM FIELD AND MEAN FIELD THEORY;129
11;Chapter 7 ANALYSIS OF MULTI-CHANNEL SUBDURAL EEG BY RECURRENT NEURAL NETWORKS;152
12;Chapter 8 MULTICRITERIA OPTIMIZATION UNDER PARAMETRIC UNCERTAINTY;173
13;Chapter 9 DESIGN OF NEURAL NETWORKS FOR PAVEMENT RUTTING;204
14;Chapter 10 NEURAL NETWORKS FOR RESIDENTIAL INFRASTRUCTURE MANAGEMENT;225
15;Chapter 11 EVACUATION SIMULATION IN UNDERGROUND MALL BY ARTIFICIAL LIFE TECHNOLOGY;259
16;Chapter 12 EPISTEMIC UNCERTAINTY AND THE MANAGEMENT OF HIGH RISK EXPOSURES;276
17;Chapter 13 EXPERIMENT WITH A HIERARCHICAL TEXT CATEGORIZATION METHOD ON WIPO PATENT COLLECTIONS;291
18;Chapter 14 STUDY OF TRANSPORTATION AND UNCERTAINTY;311
19;Chapter 15 MULTI AGENT SYSTEMS APPROACH TO PARKING FACILITIES MANAGEMENT;328
20;Chapter 16 MODELING TRANSPORTATION CHOICE THROUGH UTILITY-BASED MULTI-LAYER FEEDFORWARD NETWORKS;347
21;Chapter 17 HETEROGENEITY IN COMMUTER DEPARTURE TIME DECISION: A PROSPECT THEORETIC APPROACH;375
22;Chapter 18 Importance of Fuzzy Sets Definitions for Fuzzy Signal Controllers;405
23;Chapter 19 RELIABILITY EVALUATION OF REALISTIC STRUCTURES USING FEM;423
24;Chapter 20 SIMULATION IN RISK-BASED CODIFIED ENGINEERING DESIGN;449
25;Chapter 21 SYSTEM IDENTIFICATION AT LOCAL LEVEL UNDER UNCERTAINTY;465
26;Chapter 22 UNCERTAINTY MODELING OF CHLORIDE CONTAMINATION AND CORROSION OF CONCRETE BRIDGES;495
27;Chapter 23 REDUNDANCY ANALYSIS OF STRUCTURAL SYSTEMS;516
28;INDEX;535

Über Autor(innen)

Nii O. Attoh-Okine, University of Delaware, Newark, DE, USA / Bilal M. Ayyub, University of Maryland, College Park, MD, USA