PMU-based wide-area security assessment
This chapter discusses data-mining-based catastrophe predictors using PMU-based WASI features. The study validates the performance of the black-box models such as SVM and RF through semitransparent data-mining models such as DT and transparent models such as DT_Fuzzy. It is observed from the extensive studies of the developed data-mining-based catastrophe predictors that while switching from the black box solutions to transparent and interpretable solutions, there is an unavoidable trade-off between accuracy, reliability, and security measures. The more transparent the predictor, the easier the implementation and maintenance by human actors. Overall, the fuzzy logic-based transparent solutions are preferred over black-box solutions to ease the implementation with improved robustness and enhance their suitability for auditing process, even sacrificing the predictive performance indices.