An improved density peaks clustering algorithm based on k nearest neighbors and turning point for evaluating the severity of railway accidents
L Shi, X Yang, X Chang, J Wu, H Sun - Reliability Engineering & System …, 2023 - Elsevier
The timely and scientific assessment of railway accident severity can provide effective
support for making a suitable rescue plan. This paper proposes an improved density peaks …
support for making a suitable rescue plan. This paper proposes an improved density peaks …
HCDC: A novel hierarchical clustering algorithm based on density-distance cores for data sets with varying density
QF Yang, WY Gao, G Han, ZY Li, M Tian, SH Zhu… - Information Systems, 2023 - Elsevier
Cluster analysis is a crucial data mining technology widely used in image segmentation,
language processing, and pattern recognition. Most existing clustering algorithms cannot …
language processing, and pattern recognition. Most existing clustering algorithms cannot …
Improved k-means text clustering algorithm based on BERT and density peak
W Hu, D Xu, Z Niu - 2021 2nd Information Communication …, 2021 - ieeexplore.ieee.org
Since the K-Means algorithm was proposed, it has been widely concerned by researchers.
Its advantage lies in its simplicity and efficiency, but it also has shortcomings. Aiming at the …
Its advantage lies in its simplicity and efficiency, but it also has shortcomings. Aiming at the …
A Robust Learning Membership Scaling Fuzzy C-Means Algorithm Based on New Belief Peak
Q Yang, G Han, W Gao, Z Yang, S Zhu… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Fuzzy C-means clustering (FCM) has been a commonly used algorithm in fuzzy clustering
for decades. However, it still faces two problems: how to determine the initial cluster center …
for decades. However, it still faces two problems: how to determine the initial cluster center …