Bayesian Networks for Modeling Dredging Decisions

Abstract

This report introduces Bayesian networks and describes how they can be used to model dredging decisions when uncertainties are present. Bayesian networks are efficient representations of joint probability distributions that can be used to perform statistical inference over a large number of random variables. An example application is developed and presented for a realistic estuarine dredging decision problem to demonstrate the method. The decision model is applied to analyze the value of obtaining additional information about selected variables that are sources of uncertainty in the decision.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Oct 01, 2011
Accession Number
ADA552536

Entities

People

  • Martin T. Schultz
  • Mitchell J. Small
  • Thomas D. Borrowman

Organizations

  • Engineer Research and Development Center

Tags

Communities of Interest

  • Human Systems

DTIC Thesaurus Topics

  • Bayesian Networks
  • Cells
  • Computational Science
  • Ecology
  • Environment
  • Environmental Health
  • Environmental Protection
  • Eutrophication
  • Fish
  • Fisheries
  • Habitats
  • Information Science
  • Operations Research
  • Probability Distributions
  • Reasoning
  • Statistical Inference
  • Water Resources

Fields of Study

  • Computer science

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Aquatic Ecology
  • Statistical inference.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference