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Zixin Feng, Teligeng Yun, Yu Zhou, Ruirui Zheng and Jianjun He
Geometric mean metric learning (GMML) algorithm is a novel metric learning approach proposed recently. It has many advantages such as unconstrained convex objective function, closed form solution, faster computational speed, and interpretability over oth...
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P. Pires da Silva, Serge Sutulo and C. Guedes Soares
Sensitivity analysis is applied to ship manoeuvring mathematical models as a means of dealing with model uncertainties, and often leads to model simplifications. A rather standard 3DOF manoeuvring model was tuned with the available results of full-scale ...
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Hong Je-Gal, Seung-Jin Lee, Jeong-Hyun Yoon, Hyun-Suk Lee, Jung-Hee Yang and Sewon Kim
Ensuring operational reliability in machinery requires accurate fault detection. While time-domain vibration pulsation signals are intuitive for pattern recognition and feature extraction, downsampling can reduce analytical complexity, but may result in ...
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Bingyu Li, Lei Wang, Qiaoyong Jiang, Wei Li and Rong Huang
In view of the limitations of traditional statistical methods in dealing with multifactor and nonlinear data and the inadequacy of classical machine learning algorithms in dealing with and predicting data with high dimensions and large sample sizes, this...
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Shuai Ma, Yafeng Wu, Hua Zheng and Linfeng Gou
Aiming at engine health management, a novel hybrid prediction method is proposed for exhaust gas temperature (EGT) prediction of gas turbine engines. This hybrid model combines a nonlinear autoregressive with exogenous input (NARX) model and a moving ave...
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