An Adaptive Fault Detection Method Based on miRNA Regulation

The NSA algorithm draws inspiration from the negative selection mechanism of T cell development, but due to the simplicity of the borrowed biological model, the algorithm itself has many shortcomings, such as dynamism and vulnerability coverage, resulting in insufficient adaptability of NSA in solving practical problems. In biology, miRNA plays an important regulatory role in T cell development at the gene level. By drawing on the biological regulatory mechanism and characteristics of miRNA, enriching and improving the negative selection model, the adaptability problem in NSA algorithm can be solved, and the fault detection performance of NSA algorithm can be improved. Therefore, based on the above ideas, this paper proposes an adaptive fault detection method based on miRNA regulation and validates it in an underwater monitoring system. The experiment shows that this method effectively improves the detection rate and reduces the false alarm rate.