Risk Analysis in Military Systems using Machine Learning
By
Chetan B Shetty (1ms11cs032)
Vijay kumar Tangadagi (1ms11cs128)
Sudarshan Rai (1ms11cs112)
Department of Computer Science and Engineering
M.S.Ramaiah institute of Technology
Bangalore-560054
Abstract
There are some systems in which a small failure can lead to accidents are called safety critical systems, these accidents are very difficult to analyze. It applies for the emerging class of systems, since they are composed of many distributed and autonomous components. It is very difficult to perform risk analysis on such systems. Hence there is a need for effective techniques to find the relationships within these system. This paper explains the use of machine learning techniques to
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The term MSS is somewhat controversial. Air traffic control is most prominent and is easy. Mobile components distributed all over the world is being explained by this component. Ad-hoc fashion is used for the interaction between these components .It follows that for MSS that are being procured now, safety has a high priority this is even followed by the new kinds of autonomous component Systems used by MSS components. Here the case study is concerned with one aspect of the safety process for MSS, specifically risk analysis. It’s an important process, unfortunately performing risk analysis on MSS is not that easy. There are problems faced in MSS risk analysis, then we see possible solution. The following problems occurs during the analysis of MSS. According to some authors Condition of an MSS configuration that can lead to an accident is defined as MSS risk. And the MSS risk analysis is defined as the procedure that is used to analyze the reason for system …show more content…
This was inspired by the successful usage of the multi-agent techniques in other fields of modelling and analysis. As illustrated in the example in this case study, we have been able to show that the approach can be used to identify some risks. Challenges that remain to be resolved include the application of this technique to a wide variety of systems, scenarios and combining the results of simulation and analysis across multiple scenarios and system configurations.
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