Virtual collection for distributed photovoltaic data: Challenges, methodologies, and applications
In recent years, with the rapid development of distributed photovoltaic systems (DPVS), the
shortage of data monitoring devices and the difficulty of comprehensive coverage of …
shortage of data monitoring devices and the difficulty of comprehensive coverage of …
A systematic literature review on identifying patterns using unsupervised clustering algorithms: A data mining perspective
M Chaudhry, I Shafi, M Mahnoor, DLR Vargas… - Symmetry, 2023 - mdpi.com
Data mining is an analytical approach that contributes to achieving a solution to many
problems by extracting previously unknown, fascinating, nontrivial, and potentially valuable …
problems by extracting previously unknown, fascinating, nontrivial, and potentially valuable …
Clustering analysis through artificial algae algorithm
Clustering analysis is widely used in many areas such as document grouping, image
recognition, web search, business intelligence, bio information, and medicine. Many …
recognition, web search, business intelligence, bio information, and medicine. Many …
Spatial-temporal heterogeneity and built environment nonlinearity in inconsiderate parking of dockless bike-sharing
Although previous studies have shed light on the travel behaviour of dockless bike-sharing
(DBS) users, little research focused on their inconsiderate parking behavior. Unlike the …
(DBS) users, little research focused on their inconsiderate parking behavior. Unlike the …
Generalized nets as a tool for the modelling of data mining processes
K Atanassov - Innovative issues in intelligent systems, 2016 - Springer
Generalized Nets as a Tool for the Modelling of Data Mining Processes | SpringerLink Skip to
main content Advertisement SpringerLink Account Menu Find a journal Publish with us Track …
main content Advertisement SpringerLink Account Menu Find a journal Publish with us Track …
A multi-surrogate-assisted dual-layer ensemble feature selection algorithm
Z Jiang, Y Zhang, J Wang - Applied Soft Computing, 2021 - Elsevier
Ensemble feature selection has attracted much attention of scholars because of its good
robustness. However, existing methods on dealing with high-dimensional or large-scale …
robustness. However, existing methods on dealing with high-dimensional or large-scale …
Customized bus scheme design of large transport terminals with jointly optimization of departure time, vehicle allocation and routing
Y Wu, Z Yuan, Q Xiao, D Yang - IET Intelligent Transport …, 2023 - Wiley Online Library
The customized bus (CB) service of large transport terminals can provide passengers with
convenient transfers and door‐to‐door services, which has the potential to help ease the …
convenient transfers and door‐to‐door services, which has the potential to help ease the …
DG-means: a superior greedy algorithm for clustering distributed data
RA Haraty, A Assaf - The Journal of Supercomputing, 2024 - Springer
Clustering divides a set of objects into several classes, where each class is composed of
similar objects. Traditional centralized clustering algorithms target those objects located on …
similar objects. Traditional centralized clustering algorithms target those objects located on …
An improved k-means distributed clustering algorithm based on spark parallel computing framework
X Lu, H Lu, J Yuan, X Wang - Journal of Physics: Conference …, 2020 - iopscience.iop.org
Traditional K-means distributed clustering algorithm has many problems in clustering big
data, such as unstable clustering results, poor clustering results and low execution …
data, such as unstable clustering results, poor clustering results and low execution …
分布的自动阈值密度峰值聚类算法.
彭启慧， 宣士斌， 高卿 - Journal of Computer Engineering & …, 2021 - search.ebscohost.com
密度峰值聚类(DPC) 是一种基于局部密度的聚类方法, 在DPC 中影响算法的效果的两个基本
因素是局部密度定义和类中心选择. 针对经典DPC 在定义局部密度时没有考虑到邻域内样本点 …
因素是局部密度定义和类中心选择. 针对经典DPC 在定义局部密度时没有考虑到邻域内样本点 …