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Dimitris Fotakis, Panagiotis Patsilinakos, Eleni Psaroudaki and Michalis Xefteris
In this work, we consider the problem of shape-based time-series clustering with the widely used Dynamic Time Warping (DTW) distance. We present a novel two-stage framework based on Sparse Gaussian Modeling. In the first stage, we apply Sparse Gaussian P...
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Yichao Xu, Yufeng Zhang and Jian Zhang
Over the past few decades, rapid economic development has led to the establishment of numerous monitoring systems, resulting in the accumulation of vast amounts of monitoring data. Among these data, dynamic acceleration data stand out prominently. Howeve...
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Pinyang Zhang and Changzheng Chen
In the operation and maintenance of planetary gearboxes, the growth of monitoring data is often faster than its analysis and classification. Careful data analysis is generally considered to require more expertise. Rendering the machine learning algorithm...
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Ioannis G. Tsoulos, Alexandros Tzallas and Evangelos Karvounis
Radial basis function networks are widely used in a multitude of applications in various scientific areas in both classification and data fitting problems. These networks deal with the above problems by adjusting their parameters through various optimiza...
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Ioannis G. Tsoulos and Vasileios Charilogis
In the present work, an innovative two-phase method is presented for parameter tuning in radial basis function artificial neural networks. These kinds of machine learning models find application in many scientific fields in classification problems or in ...
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