Modeling the lane-changing behavior of non-motorized vehicles on road segments via social force model
X Hou, R Zhang, M Yang, S Cheng - Physica A: Statistical Mechanics and …, 2024 - Elsevier
Using traffic marking to separate non-motorized lane from the adjacent motorized lane is a
common traffic design method for urban road segments. With the increase in non-motorized …
common traffic design method for urban road segments. With the increase in non-motorized …
Distraction-level recognition based on stacking ensemble learning for IVIS secondary tasks
X Zhao, Z Li, C Zhao, R Fu, C Wang - Expert Systems with Applications, 2024 - Elsevier
Driver distraction-level recognition while performing secondary tasks in full-touch in-vehicle
information systems (FTIVISs) is essential for the harmonious co-driving of human and …
information systems (FTIVISs) is essential for the harmonious co-driving of human and …
Categorical Data Clustering: A Bibliometric Analysis and Taxonomy
M Cendana, RJ Kuo - Machine Learning and Knowledge Extraction, 2024 - mdpi.com
Numerous real-world applications apply categorical data clustering to find hidden patterns in
the data. The K-modes-based algorithm is a popular algorithm for solving common issues in …
the data. The K-modes-based algorithm is a popular algorithm for solving common issues in …
DPC-DNG: Graph-based label propagation of k-nearest higher-density neighbors for density peaks clustering
Y Li, L Sun, Y Tang - Applied Soft Computing, 2024 - Elsevier
Density peaks clustering (DPC) algorithm is a novel density-based clustering approach that
effectively determines cluster centers from a decision graph and groups objects by assigning …
effectively determines cluster centers from a decision graph and groups objects by assigning …
ReShape: A Universal Data Processing Approach for Clustering Inhomogeneous and Weakly Separated Manifold Data
Classical clustering methods such as k-means, spectral clustering, DBSCAN, and DPC often
operate under specific assumptions about data characteristics. However, the increasing …
operate under specific assumptions about data characteristics. However, the increasing …
An improved density peaks clustering based on sparrow search algorithm
Y Chen, J Zhou, X He, X Luo - Cluster Computing, 2024 - Springer
Density peaks clustering (DPC) algorithm has attracted the attention of scholars because of
its simplicity and efficiency. However, it certainly has some disadvantages. On the one hand …
its simplicity and efficiency. However, it certainly has some disadvantages. On the one hand …
Penentuan Pusat Klaster Secara Otomatis Pada Algoritma Density Peaks Clustering Berbasis Metode Inter Quartile Range
R Efendi, A Junaidi, AM Rizki - Jurnal Informatika dan Teknik …, 2024 - journal.eng.unila.ac.id
Clustering adalah sebuah metode untuk mengelompokkan data yang sejenis ke dalam satu
bagian yang sama. Proses ini mampu membantu manusia untuk mendapatkan informasi …
bagian yang sama. Proses ini mampu membantu manusia untuk mendapatkan informasi …
Adaptive Density Peak Clustering with Optimized Border-Peeling
H Lin, J Hou, H Yuan - International Conference on Knowledge Science …, 2024 - Springer
Abstract Density Peak Clustering (DPC) is good at processing datasets with irregular shapes
and uneven density. However, the traditional DPC algorithm has limitations in identifying …
and uneven density. However, the traditional DPC algorithm has limitations in identifying …
Knowledge Science, Engineering and Management
This five-volume set contains the papers presented at the 17th International Conference on
Knowledge Science, Engineering and Management (KSEM 2024), held during August 16 …
Knowledge Science, Engineering and Management (KSEM 2024), held during August 16 …