|
|
|
Jun Jian, Jinhai Chen and Peter J. Webster
Ship pilots and maritime safety administration have an urgent need for more accurate and earlier warnings for strong wind gusts. This study firstly investigated the ?Oriental Star? cruise ship capsizing event in 2015, one of the deadliest shipwreck event...
ver más
|
|
|
|
|
|
Christos Karras, Aristeidis Karras, Konstantinos C. Giotopoulos, Markos Avlonitis and Spyros Sioutas
In the context of big-data analysis, the clustering technique holds significant importance for the effective categorization and organization of extensive datasets. However, pinpointing the ideal number of clusters and handling high-dimensional data can b...
ver más
|
|
|
|
|
|
Li-Na Wang, Hongxu Wei, Yuchen Zheng, Junyu Dong and Guoqiang Zhong
Ensemble learning, online learning and deep learning are very effective and versatile in a wide spectrum of problem domains, such as feature extraction, multi-class classification and retrieval. In this paper, combining the ideas of ensemble learning, on...
ver más
|
|
|
|
|
|
Annwesha Banerjee Majumder, Somsubhra Gupta, Dharmpal Singh, Biswaranjan Acharya, Vassilis C. Gerogiannis, Andreas Kanavos and Panagiotis Pintelas
Heart disease is a leading global cause of mortality, demanding early detection for effective and timely medical intervention. In this study, we propose a machine learning-based model for early heart disease prediction. This model is trained on a dataset...
ver más
|
|
|
|
|
|
Ze Liu and Yaxiong Peng
Because of the impact of the complex environment of tunnel portals, the measured blasting vibration signals in a tunnel portal contains a lot of high-frequency noise. To achieve effective noise reduction, a novel method of noise reduction for blasting vi...
ver más
|
|
|