Search Results - "Liao, Mingyong"

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  1. 1

    Identifying the essential conditioning factors of landslide susceptibility models under different grid resolutions using hybrid machine learning: A case of Wushan and Wuxi counties, China by Liao, Mingyong, Wen, Haijia, Yang, Ling

    Published in Catena (Giessen) (01-10-2022)
    “…[Display omitted] •The effect of grid resolution on factors was investigated.•Three models for finding the essential factor are proposed.•The essential factors…”
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    Journal Article
  2. 2

    Different-Classification-Scheme-Based Machine Learning Model of Building Seismic Resilience Assessment in a Mountainous Region by Wen, Haijia, Zhou, Xinzhi, Zhang, Chi, Liao, Mingyong, Xiao, Jiafeng

    Published in Remote sensing (Basel, Switzerland) (22-04-2023)
    “…This study aims to develop different-classification-scheme-based building-seismic-resilience (BSR)-mapping models using random forest (RF) and a support vector…”
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    Journal Article
  3. 3

    Study on Machine Learning Models for Building Resilience Evaluation in Mountainous Area: A Case Study of Banan District, Chongqing, China by Zhang, Chi, Wen, Haijia, Liao, Mingyong, Lin, Yu, Wu, Yang, Zhang, Hui

    Published in Sensors (Basel, Switzerland) (03-02-2022)
    “…'Resilience' is a new concept in the research and application of urban construction. From the perspective of building adaptability in a mountainous environment…”
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    Journal Article
  4. 4

    Insights into spatial differential characteristics of landslide susceptibility from sub-region to whole-region cased by northeast Chongqing, China by Liu, Rui, Ding, YueKai, Sun, Deliang, Wen, Haijia, Gu, Qingyu, Shi, Shuxian, Liao, Mingyong

    Published in Geomatics, natural hazards and risk (31-12-2023)
    “…Landslides have differential characteristics in different regions. This study explores landslide susceptibility mapping (LSM) based on different evaluation…”
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    Journal Article
  5. 5

    Improving the model robustness of flood hazard mapping based on hyperparameter optimization of random forest by Liao, Mingyong, Wen, Haijia, Yang, Ling, Wang, Guilin, Xiang, Xuekun, Liang, Xiaowen

    Published in Expert systems with applications (01-05-2024)
    “…Traditional machine learning algorithms face challenges in assessing flood susceptibility reliably due to their low robustness and the inherent 'black-box'…”
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    Journal Article
  6. 6

    Rockfall susceptibility mapping using XGBoost model by hybrid optimized factor screening and hyperparameter by Wen, Haijia, Hu, Jiwei, Zhang, Jialan, Xiang, Xuekun, Liao, Mingyong

    Published in Geocarto international (13-12-2022)
    “…The accuracy of the evaluation model of rockfall susceptibility lies on reasonable conditioning factors and algorithm hyperparameters optimization. A rockfall…”
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    Journal Article
  7. 7
  8. 8

    Hybrid optimized RF model of seismic resilience of buildings in mountainous region based on hyperparameter tuning and SMOTE by Wen, Haijia, Wu, Jinnan, Zhang, Chi, Zhou, Xinzhi, Liao, Mingyong, Xu, Jiahui

    Published in Journal of Building Engineering (15-07-2023)
    “…This study aims to develop hybrid-optimized random forest (RF) model of seismic physical resilience evaluation of buildings in mountainous region. Based on the…”
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    Journal Article