Seah C, Tsang I, Ong Y, Lee K (2010) Predictive distribution matching SVM for multi-domain learning. In: Proceedings of the European conference on machine learning and principles and practice of knowledge discovery in databases, pp 231–247 Chapter Google Scholar Pan S, Kwok J, Yang Q (...
One is based on the support vector machine (SVM) with hand-crafted features, including signal features [96] or wavelet-packet energy (WPE) as Eq. 14, and the other is based on 1D-CNN with multi-channel input (shown as Fig. 22), which is similar to the DNN model used in previous ...
They used ANN and SVM for condition prediction of these chillers over three months and one year and found that ANN was more accurate, but had a longer processing time than SVM. RF is a widely used supervised learning algorithm due to its simplicity, usability, and ability to produce ...
The proposed framework leverages Conditional GANs (CGANs) alongside the Harris Hawk Optimization (HHO) metaheuristic method to optimize feature selection from input data effectively for machine learning (ML) models such as Bagged Ensemble (BE), AdaBoost (AD), Support Vector Machine (SVM), K-Nearest...
Then, the SVM was employed to complete leak recognition for de-noised leak data. Quy [17] used the spectral portrait method to pre-process pipe leak AE signals. Next, a multi-class SVM classifier was used for leak detection. In the leak detection system based on deep learning algorithms, ...