Author
Hao Lu
Bio: Hao Lu is an academic researcher from Chongqing Jiaotong University. The author has contributed to research in topics: China & Urban agglomeration. The author has co-authored 1 publications.
Papers
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TL;DR: In this article, a mixed-methods approach to urban agglomeration resilience estimation is proposed, where particle swarm optimization algorithm is used to optimize the back propagation neural network in order to evaluate the resilience of subsystems, including economy, society, environment, and science and technology resilience subsystems.
31 citations
TL;DR: In this article , an urban resilience measurement model combined with the BP neural network with a genetic algorithm is established, and the spatial-temporal evolution is analyzed by the convergence model to explore the difference among the cities in Chengdu-Chongqing Urban Agglomeration.
Abstract: An accurate assessment of urban resilience can provide decision-makers with a better understanding of urban resilience and valuable references for developing relevant urban resilience development strategies. However, most works of existing literature focus on evaluating urban resilience from a static perspective and few studies focus on the spatio-temporal evolution characteristics of urban resilience. Therefore, an urban resilience measurement model combined with the BP neural network with a genetic algorithm is established. The Chengdu-Chongqing Urban Agglomeration is taken as a case study. In addition, the spatial-temporal evolution is analyzed by the convergence model to explore the difference among the cities in Chengdu-Chongqing Urban Agglomeration. The main results of this study show that: (1) the distribution of urban resilience in Chengdu-Chongqing Urban Agglomeration has a double-headed structure, which differs from other urban agglomerations in China. (2) the four subsystems of resilience reveal exciting results that the ecological, economic and social resilience in the Chengdu-Chongqing urban agglomeration all presented a polarized pattern, and the infrastructure resilience is balanced. (3) The temporal evolution of urban agglomeration resilience indicates that the resilience gap between cities in Chengdu-Chongqing Urban Agglomeration is narrowing from 2011 to 2019.
20 citations
TL;DR: Wang et al. as discussed by the authors proposed a new assessment framework for urban resilience from the perspective of "pressure-state-response" to address this issue, and the methods of BP neural network, genetic algorithm, Moran's index and the center of gravity model were combined to establish the assessment model of urban resilience.
Abstract: It has been widely appreciated that urban resilience is one of the core goals of urban development. Various approaches for evaluating the level of urban resilience have been developed recently. However, previous urban resilience assessment studies have mainly concentrated on the economy, society, infrastructure, and ecological environment, with very few considering the characteristics of the urban resilience regression process. Therefore, this research proposes a new assessment framework for urban resilience from the perspective of “pressure-state-response” to address this issue. And then, the methods of the BP neural network, genetic algorithm, Moran's index and the center of gravity model are combined to establish the assessment model of urban resilience. 31 provinces in Mainland China are selected as a case study to demonstrate the application of the assessment model. The calculation results indicate that the urban resilience level of all provinces in China is rising, and the provincial urban resilience development shows the characteristics of fluctuation. The trend of urban resilience shifted from north to south from 2013 to 2019, consistent with China's economic center of gravity moving from north to south. This study develops a new angle for evaluating urban resilience and provides effective policies toward urban resilience.
2 citations
TL;DR: Wang et al. as discussed by the authors built a GA-SVR model to analyze the influences of speed, design brightness, measured brightness, and position in the Gaogu long tunnel, and found that the driver's psychological pressure was greatest on the entrance and exit section of the tunnel.
Abstract: Improving the driving safety of mountainous highway tunnels has become an urgent problem in China, while the existing literature pays more attention to the safety of urban tunnels. From the perspective of visual load, this paper built a GA-SVR model to analyze the influences of speed, design brightness, measured brightness, and position in the Gaogu long tunnel. The results show the following: firstly, the changes of MTPA in the long mountainous highway tunnels can be divided into five stages, which is different from the three-stage division of urban tunnels; secondly, the influencing degree of factors was varied in different stages: the position factor mattered most in stages 1, 2, 4, and 5, while the design brightness had the greatest impact in stage 3; thirdly, the driver’s psychological pressure was greatest on the entrance and exit section of the tunnel; lastly, the increased length of mountainous highway tunnels and the long-term enclosed driving environment made the psychological load of drivers intensified. Therefore, it was necessary for the mountainous highway tunnels to consider more accurate gradual lighting design in the 200-m sections after the entrance and before the exit, meanwhile enhancing traffic safety management and protections in the middle of the tunnel.
1 citations
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TL;DR: In this paper , a multi-dimensional index system that evaluates urban resilience across economic, social, institutional, ecological, and infrastructure dimensions is presented. But, the results show that the urban resilience in China slowly increased over the study period and tended to be balanced across the dimensions, although urban environmental resilience and institutional resilience were generally higher, and economic and infrastructure resilience were lower.
24 citations
TL;DR: In this paper , an evaluation index system of a resilient megacity based on water, energy, and food nexus was established to assess the resilience level of megacities, and Zhengzhou was selected as an example to study the paths and strategies for its resilience.
9 citations
TL;DR: In this article , a comprehensive evaluation model, coupling coordination degree model and panel Tobit regression model were adopted to systematically study the temporal and spatial differentiation of and influencing factors on the coupling degree between land development intensity and urban resilience in the Yangtze River Delta urban agglomeration from 2009 to 2019.
Abstract: The rapid urbanization of the Yangtze River Delta urban agglomeration has led to the convergence of population, land and capital. The coordination between land development intensity and urban resilience has become a key issue in the post-urbanization period. From the perspective of regional overall and coordinated development, we constructed an evaluation index system of land development intensity and urban resilience. Then, the comprehensive evaluation model, coupling coordination degree model and panel Tobit regression model were adopted to systematically study the temporal and spatial differentiation of and influencing factors on the coupling coordination degree between land development intensity and urban resilience in the Yangtze River Delta urban agglomeration from 2009 to 2019. The results show that from 2009 to 2019, the land development intensity exhibited a slow and fluctuating increase, while the urban resilience displayed continuous growth, and the level of land development intensity generally lagged behind that of urban resilience. From 2009 to 2019, the average coupling coordination degree between land development intensity and urban resilience in the Yangtze River Delta urban agglomeration increased from 0.5177 to 0.6626, which generally changed from bare coordination to moderate coordination. In terms of spatial distribution, the coastal cities and cities along the Yangtze River were characterized by high coupling coordination degrees, which formed a “T” shape distribution pattern. In addition, the coupling coordination types showed certain spatio-temporal heterogeneity among cities. Finally, land economic benefit, green industrial development, scientific and technological innovation, social management and infrastructure all had significant impacts on the coupling and coordination between land development intensity and urban resilience in the Yangtze River Delta urban agglomeration.
8 citations
TL;DR: Zhang et al. as discussed by the authors employed the TOPSIS method, particle swarm optimization (PSO), and extreme learning machine (ELM) to measure urban resilience from 2010 to 2020.
8 citations
TL;DR: Wang et al. as discussed by the authors explored the impact of carbon emission reduction on urban resilience and its spatial-temporal characteristics with a sample of 267 prefectural-level cities from 2006 to 2019 in China.
8 citations