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Less is More: Changing the Battle Damage Assessment Paradigm

Sgro,Joel D

2017

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  • Título:
    Less is More: Changing the Battle Damage Assessment Paradigm
  • Autor: Sgro,Joel D
  • Assuntos: algorithms ; BATTLE DAMAGE ASSESSMENT ; Battle management ; MILITARY OPERATIONS ; Military Operations, Strategy and Tactics ; PREDICTIVE ANALYTICS
  • Descrição: An important part of the execution of any military operation is the ability to quickly determine whether or not specific actions are having the desired impact on the adversary and making progress toward the commanders overarching goals. Experience in large-scale conflict over the past few decades suggests that the current Battle Damage Assessment (BDA) process has had, and will continue to have, difficulty keeping up with the pace of operations due to limited availability of required intelligence collection assets. Reliable assessment of the effectiveness and impact of military actions promises to become even more difficult as the speed and complexity of combat increases, and conflict spreads across multiple domains. Models are in use today that attempt to mix past and real-time data to predict a customers purchase activity as they are clicking through a website, to predict mechanical failures as aircraft are being serviced, and to predict the outcome of sporting events in progress. Similar models could be employed to examine available data from ongoing operations, along with testing or other past data, to determine the probable results of a strike when no traditional BDA is available. This study uses an evaluation framework, guided by traditional characteristics of good intelligence as evaluation criteria, to examine the prospect of predictive BDA. While there are both advantages and drawbacks for predictive analytics, the conclusion of this analysis is that it could provide added benefit in situations where traditional information is lacking. The Air Force should begin a low-level investment in predictive BDA algorithm development and test its accuracy and sufficiency at every opportunity in training or combat operations, with the hope that predictive analytics can help provide leaders with a more complete picture to consider when making decisions.
  • Data de criação/publicação: 2017
  • Idioma: Inglês
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  • Realização: ABCD-USP USP   Logos de Redes Sociais: Freepik

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