...., 2017a). The methods for LF range from linear, like linear regression and auto-regressive methods, to non-linear, like artificial neural networks and support vector machines, and are applied in the low, medium and high-voltage systems. Vu et al. (2014) performed a short-term load...

.../methodology/approach The data constructed by analyzing the input impedance using the finite element method are used in machine learning. From the loci of the input impedance of systems, the trained neural network (NN), support vector machine and naive Bayes classifier judge if a metal object exists...

... is proposed based on the ranked harmonic components and support vector machine classifier. Findings The proposed diagnosis approach is verified by using an experimental test. Results show that by this approach open-circuit fault on the diode rectifier can effectively be detected by the accuracy of 98.5...

.... To some extent, short-term load forecasting is more difficult in microgrids than in macrogrids. Design/methodology/approach This paper presents the method of Dragonfly Algorithm-based support vector machine (DA-SVM) to forecast the short-term load in microgrids. This method adopts the combination...