A Novel K-Means Clustering Algorithm with a Noise Algorithm for Capturing Urban Hotspots

With the development of cities, urban congestion is nearly an unavoidable problem for almost every large-scale city. Road planning is an effective means to alleviate urban congestion, which is a classical non-deterministic polynomial time (NP) hard problem, and has become an important research hotsp...

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Vydané v:	Applied sciences Ročník 11; číslo 23; s. 11202
Hlavní autori:	Ran, Xiaojuan, Zhou, Xiangbing, Lei, Mu, Tepsan, Worawit, Deng, Wu
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Basel MDPI AG 01.12.2021
Predmet:	Artificial intelligence Big Data Cluster analysis Clustering Genetic algorithms K-means clustering Noise noise algorithm non-parametric Wilcoxon statistical analysis Nonparametric statistics Research methodology Smart cities Statistical analysis taxi GPS data Traffic congestion unsupervised evaluation urban road planning
ISSN:	2076-3417, 2076-3417
On-line prístup:	Získať plný text
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