A method for false alarm recognition considering threshold
2019
A new approach to false alarm recognition is proposed. The described method divides the state of a system into three types: normal, false-alarm, and faulty, and analyzes the overlapping relations of the distribution functions of different states to determine the optimal thresholds. After a brief introduction to support vector machine (SVM), the proposed strategy based on the results using thresholds is explained. The presented evolutionary approach is illustrated by a fault injection system. The accuracy of the technique is compared with the conventional and other intelligent methods, and the obtained results are discussed.
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