Some Advancements In Monte-Carlo Integration Methods With Applications To Proximity Fuse Detection Probabilities

    Authors

    D. G. Linton;M. J. Bendickson

    Comments

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    Abbreviated Journal Title

    Comput. Ind. Eng.

    Keywords

    Computer Science, Interdisciplinary Applications; Engineering, ; Industrial

    Abstract

    A simulation model is developed for estimating any quantity defined as a multiple integral with constant, variable or infinite limits of integration. The model evaluates multiple integrals by sampling uniformally over the multidimensional volume defined by the original region of integration, and employing the sample variance (associated with Monte Carlo methods) to obtain a probabilistic representation for the error bound. Uniform sampling over any region of integration is accomplished by determining the appropriate conditional probability density functions and integrating - an approach which is not shown in the simulation literature. The calculation of detection probabilities for a proximity fuze is used to illustrate the results (and to show how such problems arise), and comparison with alternative solution procedures (e.g. Gaussian quadrature) are discussed.

    Journal Title

    Computers & Industrial Engineering

    Volume

    22

    Issue/Number

    3

    Publication Date

    1-1-1992

    Document Type

    Article

    Language

    English

    First Page

    313

    Last Page

    321

    WOS Identifier

    WOS:A1992HV37800008

    ISSN

    0360-8352

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