Urban resilience and livability performance of European smart cities: A novel machine learning approach

弹性(材料科学) 支持向量机 随机森林 机器学习 人工智能 智慧城市 公制(单位) 朴素贝叶斯分类器 聚类分析 计算机科学 工程类 物联网 计算机安全 运营管理 热力学 物理
作者
Adeeb A. Kutty,Tadesse G. Wakjira,Murat Küçükvar,Galal M. Abdella,Nuri C. Onat
出处
期刊:Journal of Cleaner Production [Elsevier BV]
卷期号:378: 134203-134203 被引量:111
标识
DOI:10.1016/j.jclepro.2022.134203
摘要

Smart cities are centres of economic opulence and hope for standardized living. Understanding the shades of urban resilience and livability in smart city models is of paramount importance. This study presents a novel two-stage data-driven framework combining a multivariate metric-distance analysis with machine learning (ML) techniques for resilience and livability assessment of smart cities. A longitudinal dataset for 35 top-ranked European smart cities from 2015 till 2020 applied as the case study under the proposed framework. Initially, a metric distance-based weighting approach is used to weight the indicators and quantify the scores across each aspect under city resilience and urban livability. The key aspects under city resilience include social, economic, infrastructure and built environment and, institutional resilience, while under urban livability, the aspects include accessibility, community well-being, and economic vibrancy. Fuzzy c-means clustering as an unsupervised machine learning technique is used to sort smart cities based on the degree of performance. In addition, an intelligent approach is presented for the prediction of the degree of livability, resilience, and aggregate performance of smart cities based on various supervised ML techniques. Classification models such as Naïve Bayes, k-nearest neighbors (kNN), support vector machine (SVM), Classification and Regression Tree (CART) and, ensemble models including Random Forest (RF) and Gradient Boosting machine (GBM) were used. Three coefficients (accuracy, Cohen's Kappa (κ) and average area under the precision-recall curve (AUC-PR)) along with confusion matrix were used to appraise the performance of the classifier ML models. The results revealed GBM as the best classification and predictive model for the resilience, livability, and aggregate performance assessment. The study also revealed Copenhagen, Geneva, Stockholm, Munich, Helsinki, Vienna, London, Oslo, Zurich, and Amsterdam as the smart cities that co-create resilience and livability in their development model with superior performance.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
魔幻友菱完成签到 ,获得积分10
刚刚
安妮完成签到 ,获得积分10
1秒前
2秒前
王12完成签到,获得积分10
2秒前
3秒前
ranj完成签到,获得积分10
4秒前
6秒前
岚12完成签到 ,获得积分10
7秒前
Wang发布了新的文献求助10
7秒前
11111完成签到 ,获得积分10
9秒前
夜话风陵杜完成签到 ,获得积分0
11秒前
13秒前
LLin完成签到,获得积分10
16秒前
风听完成签到 ,获得积分10
16秒前
咕咕完成签到 ,获得积分10
17秒前
大大怪将军完成签到,获得积分10
20秒前
朴实雨竹完成签到,获得积分10
21秒前
lx完成签到,获得积分10
22秒前
23秒前
26秒前
谷飞翔完成签到,获得积分20
27秒前
hadfunsix完成签到 ,获得积分10
29秒前
罗春燕发布了新的文献求助10
29秒前
微笑的严青完成签到,获得积分10
31秒前
32秒前
所所应助科研通管家采纳,获得30
34秒前
JamesPei应助科研通管家采纳,获得10
34秒前
34秒前
35秒前
honey完成签到 ,获得积分10
37秒前
紫色奶萨发布了新的文献求助10
39秒前
逃跑的炸鸡完成签到 ,获得积分10
40秒前
xucheng完成签到,获得积分10
42秒前
44秒前
王娜完成签到,获得积分10
44秒前
45秒前
科研通AI6.2应助罗春燕采纳,获得10
46秒前
科研通AI6.2应助dde采纳,获得10
46秒前
Yuyu完成签到 ,获得积分10
47秒前
zzz完成签到,获得积分10
47秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Les Mantodea de Guyane: Insecta, Polyneoptera [The Mantids of French Guiana] 2500
Atlas of Aligner Treatment and Planning A Case-Based Approach 1000
悉尼大学博士学位论文,题目:Modelling and testing of one-sided stitched laminated composites. 作者:Kristopher P. Plain 700
Soil mites of the family Rhagidiidae (Actinedida: Eupodoidea). Morphology, Systematics, Ecology 520
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
丝光沸石活性位点定向调控及其二甲醚羰基化性能研究 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7432707
求助须知:如何正确求助?哪些是违规求助? 9034383
关于积分的说明 19246022
捐赠科研通 7058943
什么是DOI,文献DOI怎么找? 3236604
关于科研通互助平台的介绍 2400227
邀请新用户注册赠送积分活动 2219806