Assessment of city sustainability from the perspective of multi-source data-driven

Zhou, Ying; Yi, Pingtao; Li, Weiwei; Gong, Chengju

doi:10.1016/j.scs.2021.102918

Cited by 28 publications

(13 citation statements)

References 63 publications

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“…As for the environmental dimensions, they were sourced from dimensions of the smart city vienna UT [35], criteria set for evaluating smart cities [37], assessing the effectiveness of smart transport [42], China smart city performance [38], ITU-T Y.4902/L.1602 indicator [43], smart city dimension [40], and city sustainability assessment [44]. The search data for indicators and keywords is presented in Table 1.…”

Section: Data Collectionmentioning

confidence: 99%

A Hybrid Sampling Approach for Improving the Classification of Imbalanced Data Using ROS and NCL Methods

2023

IJIES

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This research presents a novel hybrid sampling technique, implemented at the data level, to effectively address imbalanced and noisy data in classification processes. The proposed technique expertly combines two established methods, namely, the random over sampling (ROS) and neighbourhood cleaning rule (NCL) approaches, to tackle imbalance and noise issues, respectively. The study carried out an empirical evaluation of the proposed approach using crowdsourced text data that primarily emphasized the triple bottom line (TBL) dimension of a smart social, economic, and environmental city. The study used the long short-term memory (LSTM), convolutional neural networks (CNN), and CNN-LSTM classification models to validate the efficacy of the proposed hybrid sampling technique and compare its performance with other existing approaches, including ROS oversampling, NCL undersampling, synthetic minority over sampling & tomek links (SMOTE-Tomek), and synthetic minority oversampling and edited nearest neighbours (SMOTE-ENN) hybrid sampling. The results are impressive, with the ROS-NCL hybrid sampling technique achieving high accuracy rates across all three classification models, at 97.71%, 98.01%, and 98.11%, respectively. This approach provides a robust and effective solution for handling impure data and holds great promise in identifying complex data patterns in real-world classification problems.

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Section: Data Collectionmentioning

confidence: 99%

A Hybrid Sampling Approach for Improving the Classification of Imbalanced Data Using ROS and NCL Methods

2023

IJIES

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“…Numerous smart city assessment models have emerged, encompassing paradigms like Sustainable Development Indicators [7,8], Lisbon ranking for smart sustainable cities [9], Smart City Performance [10], IESE Cities in Motion Index [11], ITU-T Y.4903/L.1603 Indicators [12], Sustainability Perspectives Indicators [13], Smart City Index Master Indicators Survey [14,8], Dimensions of the Smart City Vienna UT [15], Characteristics of Smart City Indicators [16], Criteria set for evaluating 2 smart cities [17], China smart city performance [18], Juniper analysis of smart city frameworks [19], Assessing the Effectiveness of Smart Transport [20], Smart City Dimension [21], and City Sustainability Assessment [22]. These models draw from a range of resources, including primary and secondary data [23].…”

Section: Introductionmentioning

confidence: 99%

An Assessment Model for Sustainability City Using Crowdsourced Data Based on General System Theory: A Design Science Methodology Approach

Ependi,

Rochim,

Wibowo

2023

Preprint

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Historically, the lack of comprehensive and real-time data is the main challenge in city sustainability assessments. However, with the increase in the availability of crowdsourced data over the last decade, a rich and real-time data source provides detailed images of urban systems. This has opened up new opportunities for practitioners, including geographers, social researchers, and data scientists, to gather and utilize social media data as a core source for studying cities and assessing their sustainability. This paper proposes an assessment model for the sustainability of cities based on crowdsourced data and the principles of General System Theory. The model aims to utilize crowdsourced data for the analysis and decision-making processes to enhance the sustainability and resilience of smart future cities.

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“…However, a large amount of the current literature is devoted to studying urban sustainability assessment or smart city assessment (Yi et al, 2021a;Zhou et al, 2021;Yi et al, 2021b;Ozkaya & Erdin, 2020), and few studies address the sustainability assessment of smart cities. In addition to focusing on the three pillars of economic aspect, environmental aspect, and social aspect, the assessment of smart cities also has requirements for the city's architectural form and the level of infrastructure construction (Bibri, 2018a;Sharma et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

An Assessment Model Of Smart City Sustainable Development: Integrating Approach With Z-DEMATEL And Z-TOPSIS-AL

Shao

Jiang

et al. 2022

Preprint

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With the intensification of urbanization, the application of contemporary technology to make cities smarter is the key to their sustainable development (SD). This study aims to propose a comprehensive assessment framework for the SD of smart cities. First, an assessment system with 5 dimensions and 25 indicators is proposed in this paper. Second, a Z fuzzy-based multiple criteria decision-making (MCDM) model is developed to clarify the internal influence of the indicators and to determine the SD performance of smart cities. The Z-DEMATEL (decision-making trial and evaluation laboratory) technique was used to determine the mutual influence relationship of the indicator and their influence weights. Moreover, this paper selected one well-known city in China as a case study and used the Z-TOPSIS-AL (technique for order preference by similarity to ideal solution based on aspiration level) approach for analysis. The results demonstrate that quality of life, per capita GDP, and GDP growth rate are the top three indicators, which means that decision-makers should pay more attention to these indicators when constructing and managing a smart city. This study provides a reference for follow-up related research, and the management findings provide a basis for managers to make decisions on the development of smart cities.

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Assessment of city sustainability from the perspective of multi-source data-driven

Cited by 28 publications

References 63 publications

A Hybrid Sampling Approach for Improving the Classification of Imbalanced Data Using ROS and NCL Methods

A Hybrid Sampling Approach for Improving the Classification of Imbalanced Data Using ROS and NCL Methods

An Assessment Model for Sustainability City Using Crowdsourced Data Based on General System Theory: A Design Science Methodology Approach

An Assessment Model Of Smart City Sustainable Development: Integrating Approach With Z-DEMATEL And Z-TOPSIS-AL

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