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A Decision Support Architecture for Maritime Operations Exploiting Multiple METOC Centres and Uncertainty

A Decision Support Architecture for Maritime Operations Exploiting Multiple METOC Centres and Uncertainty

Raffaele Grasso, Marco Cococcioni, Michel Rixen, Alberto Baldacci
Copyright: © 2013 |Pages: 23
ISBN13: 9781466624733|ISBN10: 1466624736|EISBN13: 9781466624740
DOI: 10.4018/978-1-4666-2473-3.ch001
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MLA

Grasso, Raffaele, et al. "A Decision Support Architecture for Maritime Operations Exploiting Multiple METOC Centres and Uncertainty." Management Theories and Strategic Practices for Decision Making, edited by Madjid Tavana, IGI Global, 2013, pp. 1-23. https://doi.org/10.4018/978-1-4666-2473-3.ch001

APA

Grasso, R., Cococcioni, M., Rixen, M., & Baldacci, A. (2013). A Decision Support Architecture for Maritime Operations Exploiting Multiple METOC Centres and Uncertainty. In M. Tavana (Ed.), Management Theories and Strategic Practices for Decision Making (pp. 1-23). IGI Global. https://doi.org/10.4018/978-1-4666-2473-3.ch001

Chicago

Grasso, Raffaele, et al. "A Decision Support Architecture for Maritime Operations Exploiting Multiple METOC Centres and Uncertainty." In Management Theories and Strategic Practices for Decision Making, edited by Madjid Tavana, 1-23. Hershey, PA: IGI Global, 2013. https://doi.org/10.4018/978-1-4666-2473-3.ch001

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Abstract

Maritime operations are affected significantly by meteorological and oceanographic (METOC) conditions. The availability of multiple METOC centres able to deliver more accurate forecasts in the near future (2/3 days) is a promising resource toward better operational planning. However, how a specific maritime operation can benefit from such forecasts is not straightforward. A decision support architecture is required to combine METOC forecasts and human knowledge and select the best action from a set of pre-defined actions for the maritime operation. This paper describes a decision support architecture developed at the NATO Undersea Research Centre that is an improvement over a previous version in two ways: (1) it exploits forecasts coming from more than one METOC centre, and (2) it exploits uncertainty associated with METOC forecasts. The former allows for the exploitation of different abilities of METOC centres at different conditions. The latter allows for the propagation of input uncertainty on output products (the risks related to each action), thus allowing operators to assess if risks related to different actions are statistically different. Both features increase the robustness of the previous decision support architecture. The effectiveness of the new architecture is demonstrated on an underwater glider surfacing experiment carried out on data collected during a cruise in the Adriatic Sea in 2006.

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