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Uncertainty Modeling and Analysis in Engineering and the Sciences
Uncertainty Modeling and Analysis in Engineering and the Sciences

Author: Bilal M. Ayyub, George J. Klir

ISBN: 9781584886440

Documents: 15

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    BookerJane.paper
    Course: ACAS 00
    School: George Mason

    THE ROLE OF EXPERT KNOWLEDGE IN UNCERTAINTY QUANTIFICATION (ARE WE ADDING MORE UNCERTAINTY OR MORE UNDERSTANDING?) Jane M. Booker Los Alamos National Laboratory MS P946 Los Alamos, NM 87545 Mark C. Anderson Los Alamos National Laboratory MS D411 Los

  • Lecture 3 Ch 3
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    Lecture 3 Ch 3
    Course: CHM 320
    School: N. Arizona

    Chapter 3 Experimental Error Homework Due Friday January 27 Problems: 3-2, 3-5, 3-9, 3-10, 3-11, 3-12, 3-14, 3-19 Lecture 3 Chapt. 3 Chapter 3 Experimental Error Uncertainties They are everywhere! We need to learn to understand them, manage them

  • Econ 4010 Lecture 8
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    Econ 4010 Lecture 8
    Course: ECON 4010
    School: USC

    5. Uncertainty: Theories of Uncertainty Surprisingly, uncertainty has a rather short history in economics. The very idea that uncertainty might be relevant for economic analysis was only really suggested in 1921, Risk, Uncertainty and Pro

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    0610040
    Course: C 060706
    School: Stanford

    XXVI Physics in Collison, Bzios, Rio de Janeiro, 6-9 July 2006 u 1 s Determinations from Jets and Scaling Violations at HERA T. Kluge DESY, Notkestr. 85, 22607 Hamburg, Germany A review is given on recent s determinations from the H1 and ZEUS Colla

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    a3
    Course: P 31
    School: JMU

    106 APPENDIX 3: Establishing Uncertainty Every number used in the laboratory must be recorded with an uncertainty. This appendix will discuss methods for obtaining that uncertainty. This section should be used in conjunction with the Error Analysis

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    ch5
    Course: ETD 12062002
    School: Virginia Tech

    Chapter 5. Application to the CERES Instrument Model This chapter provides an example of the application of the statistical protocol developed in Chapter 3 and validated in Chapter 4. The theory is applied to a MCRT model of the CERES (Clouds and th

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    bityukov
    Course: C 0405241
    School: Stanford

    Uncertainties in estimation of quality of planned experiments S.I. Bityukov1,2, N.V. Krasnikov Institute for nuclear research RAS, Prospect 60-letiya Octyabrya, 117312 Moscow, Russia 1 Institute for high energy physics, 142281 Protvino, Russia 2 ht

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    cressie
    Course: WS 5
    School: Ohio State

    Uncertainty in Ecological Analysis Noel Cressie Director, Program in Spatial Statistics and Environmental Sciences The Ohio State University (www.stat.ohio-state.edu/sses) Uncertainty in Ecological Analysis p.1/26 The Workshop Science MBI Organi

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    WhitingPresentation
    Course: NOV 05
    School: Illinois Tech

    Using risk assessments to set performance objectives and performance criteria that achieve a food safety objective ICMSF/RAC/ILSI/IAFP/IFT Symposium on Relating Microbiological Testing and Microbiological Criteria to Public Health Goals Richard C. W

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    Howard_etal_2008
    Course: SYMP 2008
    School: ASU

    Water Managers Strategies for Addressing Uncertainty in Their Use of GIS for Decision-Making Jason Howard, Kelli Larson, Dave White, and Elizabeth Wentz Arizona State University, Decision Center for a Desert City Abstract Water managers in the Phoen

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    Phys174-Ex2
    Course: P 174
    School: Maryland

    Exercise 2 Measurements: Their Errors and Uncertainties I. Purpose The main purpose of this exercise is to teach you how to estimate the size of random errors and uncertainties when making measurements. You will learn what we mean by the error in a m

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    Uncertainty_Analysis
    Course: MEGR 6181
    School: UNC Charlotte

    Uncertainty Analysis GUM Method Uncertainty in Measurement Uncertainty is a parameter, associated with the result of a measurement, that characterizes the dispersion of the values that could reasonably be attributed to the measurand.* * The term mea

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    TRB02UrbanSim
    Course: CE 02
    School: University of Texas

    Uncertainty Propagation in an Integrated Land Use-Transportation Modeling Framework: Output Variation via UrbanSim Anant Pradhan Graduate Student Researcher The University of Texas at Austin. 6.9 E. Cockrell Jr. Hall Austin, TX 78712-1076. Email: ana

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    Wildey
    Course: AFFILIATES 2007
    School: University of Texas

    Project Goals Stochastic Methods Model Problem Future Work Uncertainty Quantification and Error Estimation T. M. Wildey1 1 Center for Subsurface Modeling Institute for Computational and Engineering Sciences The University of Texas October 23, 2007

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    analysisofexperimentaluncertainty
    Course: ME 461
    School: Wisconsin

    Analysis of Experimental Uncertainty (From ME370 Lab Notebook) References Introduction to Fluid Mechanics, Fox, R.W. and McDonald, A.T., John Wiley & Sons, 4th edition, 1992, Appendix F. Taylor B.N. and Kuyatt, C.E., Guidelines for Evaluating and Exp

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