2021
DOI: 10.1371/journal.pone.0248503
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Wind disasters adaptation in cities in a changing climate: A systematic review

Abstract: Wind-related disasters will bring more devastating consequences to cities in the future with a changing climate, but relevant studies have so far provided insufficient information to guide adaptation actions. This study aims to provide an in-depth elaboration of the contents discussed in open access literature regarding wind disaster adaptation in cities. We used the Latent Dirichlet Allocation (LDA) to refine topics and main contents based on 232 publications (1900 to 2019) extracted from Web of Science and S… Show more

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Cited by 13 publications
(8 citation statements)
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References 193 publications
(216 reference statements)
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“…Imbalanced data is one of the important problems to be solved in machine learning and data mining. Imbalance data classification is widely used in data processing in the fields of social surveys, disaster prediction and disease prevention [1][2][3]. Studies have shown that in the classification process of imbalanced data, the classification hyperplane boundary is shifted to the side of small samples due to the support of large sample size, and then small samples are misclassified leading to low classification accuracy of imbalanced data.…”
Section: Introductionmentioning
confidence: 99%
“…Imbalanced data is one of the important problems to be solved in machine learning and data mining. Imbalance data classification is widely used in data processing in the fields of social surveys, disaster prediction and disease prevention [1][2][3]. Studies have shown that in the classification process of imbalanced data, the classification hyperplane boundary is shifted to the side of small samples due to the support of large sample size, and then small samples are misclassified leading to low classification accuracy of imbalanced data.…”
Section: Introductionmentioning
confidence: 99%
“…Finally, spectral analysis techniques can serve to estimate wind climate conditions several months in advance, with adequate sampling frequency these techniques could be of great applicability for seasonal and sub‐seasonal wind forecasting (Lledó et al., 2019), as well as to the study of extreme wind events such as wind droughts (Lledó et al., 2018). This is crucial for decision makers in order to reduce the socioeconomic and environmental implications of weak or strong wind conditions, and to establish short‐term adaptation to wind change and variability (He et al., 2021).…”
Section: Discussionmentioning
confidence: 99%
“…However, some publications refer mainly to storm risks. These papers most often show the impacts of strong, stormy sea winds on cities located in the coastal zone [37][38][39][40][41] or focus on the impact of urban air on the health of residents [42,43]. In turn, in the category of the impact of wind on cities, large urban agglomerations, such as Delhi [44][45][46][47], are most often included.…”
Section: Threats To the Sustainable Development Of Cities And Townsmentioning
confidence: 99%