Aerial Threat Perception Architecture Using Data Mining

Anwar‐ul‐Haq, Muhammad; Malik, Asad Waqar; Khan, Shoab Ahmed

doi:10.1007/978-3-642-14292-5_31

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2012

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“…When we have the classification identifiers, classification groups and data mining approach selected we built architecture [8] for collecting the results. This architecture uses the mixture of many confidence factors for the prediction.…”

Section: Methodsmentioning

confidence: 99%

Confidence Factor Variations for Aerial Threat Perception

Anwar‐ul‐Haq¹

2012

IJIEE

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This paper presents confidence factor variations for simulated threat perception architecture contributing a better way to quantify the results for threat perception accuracy. Our technique incorporates using data mining algorithms to find effective data patterns and matching the flight parameters with these patterns to give a percentage match. A confidence criterion is proposed to depict these results effectively and show variations for aerial threat prediction. We conclude that maximum confidence percentage can be achieved by using the maximum confidence factors. Each confidence factor returns maximum confidence when offsets and increments close to zero which is the ideal match brings the return.

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Section: Methodsmentioning

confidence: 99%