A Machine Learning Approach to Predict Site Selection from the Perspective of Vitality Improvement DOI Creative Commons
Bin Zhao, Hao Zheng, Xuesong Cheng

и другие.

Land, Год журнала: 2024, Номер 13(12), С. 2113 - 2113

Опубликована: Дек. 6, 2024

The selection of construction sites for Cultural and Museum Public Buildings (CMPBs) has a profound impact on their future operations development. To enhance site planning efficiency, we developed predictive model integrating Artificial Neural Networks (ANNs) Genetic Algorithms (GAs). Taking Shanghai as our case study, utilized over 1.5 million points interest data from Amap Visiting Vitality Values (VVVs) Dianping Shanghai’s administrative area map. We analyzed compiled 344 sites, each containing 39 infrastructure sets one visit vitality set the ANN input. was then tested with untrained to predict VVVs based input sets. conducted multi-precision analysis simulate various scenarios, assessing model’s applicability at different scales. Combining GA approach, predicted improvements. This method can significantly contribute early planning, design, development, operational management CMPBs in future.

Язык: Английский

Evaluation of Urban Infrastructure Resilience Based on Risk–Resilience Coupling: A Case Study of Zhengzhou City DOI Creative Commons
Wenli Dong,

Yunhan Zhou,

Dongxin Guo

и другие.

Land, Год журнала: 2025, Номер 14(3), С. 530 - 530

Опубликована: Март 3, 2025

The frequent occurrence of disasters has brought significant challenges to increasingly complex urban systems. Resilient city planning and construction emerged as a new paradigm for dealing with the growing risks. Infrastructure systems like transportation, lifelines, flood control, drainage are essential operation during disasters. It is necessary measure how risks affect these systems’ resilience at different spatial scales. This paper develops an infrastructure risk evaluation index system in areas based on characteristics. Then, comprehensive established risk–resilience coupling mechanism. overall characteristics then identified. transmission level causes effects analyzed principle scale. Additionally, enhancement strategies under scenarios proposed. In empirical study Zhengzhou City, shows clustering area. high central low periphery. Specifically, it relatively southern northwestern parts airport economy zone (AEZ) center. leading driving factors drought, hazardous materials, infectious diseases, epidemics, while include transportation networks, sponge construction, municipal pipe fire protection. proposes “risk-resilience” framework evaluate analyze multi-hazard multi-system across multi-level provides strategies, complementing existing individual dimensional or studies. findings could offer visualized results support decision-making Zhengzhou’s resilient outline special provide references assessment similar cities.

Язык: Английский

Процитировано

1

Exploring the low-carbon development path of resource-based cities based on scenario simulation DOI Creative Commons

Liyong Cao,

Peian Chong

Scientific Reports, Год журнала: 2025, Номер 15(1)

Опубликована: Фев. 18, 2025

Abstract Resource-based cities (RBCs) have historically been constrained by their inherent characteristics, impeding rapid shifts in energy consumption patterns and exerting substantial pressure on regional decarbonization efforts. Herein, 18 RBCs southwestern China were taken as the research object. Firstly, a resilience index system was constructed for resource ecosystem socio-economic of RBCs, optimization mutation level algorithm used to measure each city. Secondly, an interval prediction model established carbon emissions based GA-DBN-KDE algorithm. Finally, setting 16 scenarios, emission range “carbon peak” time Southwest from 2023 2040 predicted, scientific path low-carbon development explored under differentiated scenarios. The results indicated that: (1) urban levels both rise; (2) demonstrated excellent performance; (3) simulation scenarios revealed varying specific paths achieve peak, underscoring necessity city-specific policy formulation. Overall, this paper provides new analytical method transformation further forging basis decision-makers formulate reduction measures.

Язык: Английский

Процитировано

1

Dynamic Monitoring and Evaluation of Ecological Environment Quality in Urumqi Metropolitan Based on Google Earth Engine DOI
Shaojie Bai,

Abudukeyimu Abulizi,

Junxia Wang

и другие.

Springer proceedings in physics, Год журнала: 2025, Номер unknown, С. 57 - 76

Опубликована: Янв. 1, 2025

Язык: Английский

Процитировано

0

Multi-scale Quantification and Optimization of Spatial Resilience under Industrial Activities: A Case Study of Resource-Based Cities in China DOI
Ya‐Ping Zhang, Jianjun Zhang, Edward Randal

и другие.

Sustainable Cities and Society, Год журнала: 2025, Номер unknown, С. 106487 - 106487

Опубликована: Май 1, 2025

Язык: Английский

Процитировано

0

Can new consumption promote urban industrial resilience? Empirical evidence from pilot cities of information consumption DOI Creative Commons
Chao Han,

Hang Su

PLoS ONE, Год журнала: 2025, Номер 20(5), С. e0323101 - e0323101

Опубликована: Май 28, 2025

The rapid advancement of digital technology and its widespread application have led to digitalization, personalization, customization in the demand side China’s economy. Enhancing industrial resilience through new types consumption is great practical significance for expanding domestic promoting high-quality, sustainable economic growth China. This study examines impact Information Consumption Pilot City (ICPC) policy as a quasi-natural experiment on urban resilience, employing difference-in-difference (DID) method empirical analysis. findings reveal that ICPC significantly enhances level resilience. Heterogeneity tests indicate this enhancement effect particularly pronounced eastern, central, larger regions. Furthermore, primarily strengthens three mechanisms: information development, entrepreneurial agglomeration, financial effects. contributes literature economy, evaluates impacts pilot policies consumption, offers valuable implications policymakers.

Язык: Английский

Процитировано

0

Assessment of urban flood resilience and obstacle factors identification: A case study of three major urban agglomerations in China DOI
Yi Xiao,

Xi Rao,

Ming Chang

и другие.

Ecological Indicators, Год журнала: 2025, Номер 176, С. 113659 - 113659

Опубликована: Май 28, 2025

Язык: Английский

Процитировано

0

Bridging digital and ecological resilience: Spatiotemporal dynamics and coordinated development paths in the Yellow River Inverted U-Shaped Belt Metropolitan Area DOI
Xufeng Cui,

Bai Fu,

Yujia Chen

и другие.

Journal of Environmental Management, Год журнала: 2025, Номер 388, С. 125990 - 125990

Опубликована: Июнь 2, 2025

Язык: Английский

Процитировано

0

Resilience assessment of urban connected infrastructure networks DOI Creative Commons
Wei Liu, Xisheng Huang, Bin Liang

и другие.

Scientific Reports, Год журнала: 2025, Номер 15(1)

Опубликована: Июнь 5, 2025

Язык: Английский

Процитировано

0

Coupling Coordination of Urban Resilience and Urban Land Use Efficiency in Hunan Province, China DOI Open Access
Shuangfei Zhao, Wei Zeng,

Da Hsuan Feng

и другие.

Sustainability, Год журнала: 2024, Номер 16(24), С. 10860 - 10860

Опубликована: Дек. 11, 2024

Urban resilience and urban land use efficiency are inevitable topics in planning development, the coupling coordination between two will contribute substantially to sustainability. With panel data from 14 cities Hunan 2010 2021 by combining entropy method, Super-SBM model, degree this study analyzed dynamic spatial–temporal evolution pattern of utilization their through a multi-dimensional evaluation index system 2021. The main findings were as follows: overall, stayed low over years study. Temporally, mean increased gradually 0.1962 0.3331, spatially, was higher eastern region than western area province, with Changsha having highest level resilience. Second, rose volatility 0.7162 0.9299, northern southern region, Zhangjiajie efficiency. Third, province had high efficiency, average value 0.8531, degrees observed Chang–Zhu–Tan agglomeration province. Fourth, moderate across rising 0.5788 0.6453, marginally coordinated primarily coordinated, where degree. All state level. highly state. research here is expected provide some references for administrators beyond release policies that achieve stronger resilience, better coordination.

Язык: Английский

Процитировано

2

A Machine Learning Approach to Predict Site Selection from the Perspective of Vitality Improvement DOI Creative Commons
Bin Zhao, Hao Zheng, Xuesong Cheng

и другие.

Land, Год журнала: 2024, Номер 13(12), С. 2113 - 2113

Опубликована: Дек. 6, 2024

The selection of construction sites for Cultural and Museum Public Buildings (CMPBs) has a profound impact on their future operations development. To enhance site planning efficiency, we developed predictive model integrating Artificial Neural Networks (ANNs) Genetic Algorithms (GAs). Taking Shanghai as our case study, utilized over 1.5 million points interest data from Amap Visiting Vitality Values (VVVs) Dianping Shanghai’s administrative area map. We analyzed compiled 344 sites, each containing 39 infrastructure sets one visit vitality set the ANN input. was then tested with untrained to predict VVVs based input sets. conducted multi-precision analysis simulate various scenarios, assessing model’s applicability at different scales. Combining GA approach, predicted improvements. This method can significantly contribute early planning, design, development, operational management CMPBs in future.

Язык: Английский

Процитировано

1