| Popis: |
Uncertainty plays decisive role in the confidence of the decisions made about events. For example, in situation awareness, decision-making is faced with two types of uncertainties; information uncertainty and data uncertainty. Data uncertainty exists due to noise in sensor measurements and is classified as randomness. Information uncertainty is due to ambiguity of using (words) to describe events. This uncertainty is known as fuzziness. Typically, these two types of uncertainties are handled separately using two different theories. Randomness is modeled by probability theory, while fuzzy-logic is used to address fuzziness. In this paper we used the Cloud computation theory to treat data randomness and information fuzziness in one single model. First, we described the Cloud theory then used the theory to generate one and two-dimensional Cloud models. Second, we used the Cloud models to capture and process data randomness and fuzziness in information relative to decision-making in situation awareness. Finally, we applied the models to generate security decisions for security monitoring of sensitive area. Testing results are reported at the end of the paper. |
