基于运动指数的k均值和分层聚类在智慧城市2022水平确定中的实现

Nissa Shahadah Qur'ani, Arie Wahyu Wijayanto
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引用次数: 0

摘要

智慧城市是具有创新发展理念的城市。然而,并不是所有国家的智慧城市都有相同的标准,因为它们是异质的。因此,采用聚类分析对智慧城市进行分类。结果表明,智慧城市分为高、低两个层次。本研究采用K-means和分层聚类方法。这个分组是基于运动指数,运动指数包括经济、环境、动员和运输指标,以及由各种变量代表的国际概况。本研究希望某一层次的智慧城市能够与其他层次的智慧城市进行比较,从而在更高层次上对智慧城市进行改进和相互学习。这也可以鼓励其他城市朝着智慧城市的方向发展。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Implementation of K-Means and Hierarchical Clustering in Determining Levels of Smart City 2022 Based on Motion Index
Smart City is a city with an innovative development concept. However, not all Smart Cities in countries have the same standard because they are quite heterogeneous. Thus, a cluster analysis was carried out to classify Smart City. The result shows that Smart City is divided into two levels, those are high and low. k-means and hierarchical clustering is used for the method of this research. The grouping is based on the motion index, which consists of economic, environmental, mobilization and transportation indicators, and also international profiles represented by various variables. This research expects that Smart City at a certain level can be compared with other levels, in order to there are improvements and mutual learning about Smart City at a high level. This can also encourage other cities in the process towards Smart City.
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