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Synopsis
Simulation modeling is used in many situations. Simulation meta-modeling is used to estimate a simulation model result by representing the space of simulation model responses. Metamodeling methods are particularly useful when the simulation model is not particularly suited to real-time or mean real-time use. Most metamodeling methods provide expected value responses while some situations need probabilistic responses. This research establishes the viability of Dynamic Bayesian Networks for simulation metamodeling, those situations needing probabilistic responses. A bootstrapping method is introduced to reduce simulation data requirement for a DBN, and experimental design is shown to benefit a DBN used to represent a multi-dimensional response space. An improved interpolation method is developed and shown beneficial to DBN metamodeling applications. These contributions are employed in a military modeling case study to fully demonstrate the viability of DBN metamodeling for Defense analysis application.
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Dynamic Bayesian Networks as a Probabilistic Metamodel for Combat Simulation
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Createspace Independent Publishing Platform, 2015
ISBN 10: 1507563043
ISBN 13: 9781507563045
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Dynamic Bayesian Networks as a Probabilistic Metamodel for Combat Simulation (Paperback)
Published by
Createspace Independent Publishing Platform, 2015
ISBN 10: 1507563043
ISBN 13: 9781507563045
New
Paperback
Seller: CitiRetail, Stevenage, United Kingdom
Seller rating 5 out of 5 stars
Paperback. Condition: new. Paperback. Simulation modeling is used in many situations. Simulation meta-modeling is used to estimate a simulation model result by representing the space of simulation model responses. Metamodeling methods are particularly useful when the simulation model is not particularly suited to real-time or mean real-time use. Most metamodeling methods provide expected value responses while some situations need probabilistic responses. This research establishes the viability of Dynamic Bayesian Networks for simulation metamodeling, those situations needing probabilistic responses. A bootstrapping method is introduced to reduce simulation data requirement for a DBN, and experimental design is shown to benet a DBN used to represent a multi-dimensional response space. An improved interpolation method is developed and shown benecial to DBN metamodeling applications. These contributions are employed in a military modeling case study to fully demonstrate the viability of DBN metamodeling for Defense analysis application. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Seller Inventory # 9781507563045
Quantity: 1 available