Please use this identifier to cite or link to this item: https://hdl.handle.net/11681/7023
Title: Bayesian networks for modeling dredging decisions
Authors: Schultz, Martin T.
Small, Mitchell J.
Borrowman, Thomas David
Keywords: Dredging--Decision making--Mathematical models
Bayesian statistical decision theory
Publisher: Environmental Laboratory (U.S.)
Engineer Research and Development Center (U.S.)
Series/Report no.: Technical Report (Engineer Research and Development Center (U.S.)) ; no. ERDC/EL TR-11-14
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.
Description: Technical Report
Gov't Doc #: ERDC/EL TR-11-14
Rights: Approved for Public Release; Distribution is Unlimited
URI: http://hdl.handle.net/11681/7023
Appears in Collections:Technical Report
Technical Report

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