Interval type-2 fuzzy-logic-based decision fusion system for air-lane monitoring

Interval type-2 fuzzy-logic-based decision fusion system for air-lane monitoring

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Eliminating mishaps due to human error is a primary focus of the avionics industry. Air-lane monitoring is critical to avert occurrences of such mishaps and is achieved using intelligence imparting techniques. Fuzzy logic is one such technique, which incorporates human knowledge for decision making with ease. Type-1 fuzzy logic for decision fusion is established to be advantageous for air-lane monitoring considering sensor input data. Decision making capabilities of type-1 systems are inconsistent when uncertainties or noise is present in the input data. To overcome this issue, this study discusses on interval type-2 fuzzy logic-based decision fusion software (IT2FLDS) for air-lane monitoring. IT2FLDS is realised using an interval type-2 Mamdani model. Experimental results presented prove that IT2FLDS exhibits better decision making capabilities when compared with type-1 fuzzy logic systems considering uncertainties in input sensor data. IT2FLDS is further extended to include flight level parameters for air-lane monitoring. Results presented prove that IT2FLDS works better than its type-1 counterpart when flight level examples are considered. Using type-2 fuzzy logic systems for avionics problems related to air-lane discipline is advocated.


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