(Input) Size Matters for CNN Classifiersdoi:10.1007/978-3-030-86340-1_11Mats L. RichterWolf ByttnerU. KrumnackAnna WiedenrothLudwig SchallnerJustin ShenkArXiv
This paper used massive inputs, including rotor angle, speed and power of generators, and formed a series of mathematical formulae using these parameters for prediction of stability. At last, by using the confidence level of ensemble classifiers (C5.0 DT, ELM, Boosting C5.0, and RF), layers...
These features are subsequently used as input to machine learning classifiers such as Random Forest (RF) or Support Vector Machine (SVM) ([15,16,17,18]). In recent years, the application of deep learning models, particularly Convolutional Neural Networks (CNNs), for PolSAR image segmentation ...