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  1. 1561

    Participatory modelling across Kenyan villages facilitates insights into the complexity of human–elephant interactions by Lynn Von Hagen, Steven A. Gray, Bruce A. Schulte, Mwangi Githiru, Helena I. Kiute, Christopher A. Lepczyk

    Published 2025-01-01
    “…Multiple variables such as road infrastructure (drivers) and soil compaction (consequences) were identified as aspects of conflicts that are under-reported or absent in scientific literature, as well as potential socio-cultural indicators. …”
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    Human–wildlife interactions by C. Rosell, F. Llimona

    Published 2025-02-01
    “…This factor is the main explanatory variable in the model. The paper provides an excellent example of how the synergies of diverse human elements in the landscape (maize croplands and roads in this case) affect the location and dimensions of these types of conflicts. …”
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    Modeling habitat suitability for endangered herb (Salvia leriifolia Benth) using Innovative hybrid machine learning algorithms by Emran Dastres, Hamidreza Rabiei-Dastjerdi, Hassan Esmaeili, Mahdis Amiri, Ali Sonboli, Mohammad Hossein Mirjalili

    Published 2025-06-01
    “…Using GIS, we compiled a dataset of 23 environmental and anthropogenic variables. Variable importance was assessed via Elastic Net (ENET), while model performance was evaluated using ROC-AUC metrics. …”
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    Determinants of crash injury severity for delivery riders: Insights from an error components mixed logit model with heterogeneous means and variances by Thanapong Champahom, Chamroeun Se, Wimon Laphrom, Sajjakaj Jomnonkwao, Rattanaporn Kasemsri, Vatanavongs Ratanavaraha

    Published 2025-07-01
    “…The rapid growth of e-commerce and food delivery services has led to an increase in commercial motorcycle riders, raising concerns about their safety on the road. This study aims to identify and analyze the determinants of crash injury severity for delivery riders in Thailand. …”
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  13. 1573

    Vulnerability of peatland fires in bengkalis regency during the ENSO El nino phase using a machine learning approach by Fauziah, Lilik B. Prasetyo, Nonon Saribanon, Nur Hayati

    Published 2025-06-01
    “…The five main factors influencing peatland fires were road density, precipitation, drainage density, NDMI, and river density. …”
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  14. 1574

    Interpretable GBDT Model for Analysing Ridership Mechanisms in Urban Rail Transit: A Case Study in Shenzhen by Wenjing Wang, Haiyan Wang, Jian Xu, Chengfa Liu, Shipeng Wang, Qing Miao

    Published 2025-03-01
    “…Utilising Automatic Fare Collection (AFC) data and multiple built environment variables, we identify six key factors (office type, accessibility, road network density, floor area ratio (FAR), public services, and residential type) through SHapley Additive exPlanations (SHAP) value and partial dependency plot (PDP) analysis. …”
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    A Comparative Study on Developing the Hybrid-Electric Vehicle ‎Systems and its Future Expectation over the Conventional Engines Cars by Medhat Elkelawy, Hagar Alm ElDin Mohamad, Mohamed Samadony, Ahmed Elbanna, Ahmed Safwat

    Published 2022-12-01
    “…In 2008, the transportation sector accounted for about 22% of total world CO2 emissions. Within this sector, road vehicles dominate oil consumption and represent 81% of total transportation energy demand. …”
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