Saltar al contenido principal

ETHNOS_APP

Inicio • Búsqueda • Revistas • Lista 0

Swastika Barua

Datos Biográficos

ID4616838
NOMBRESwastika Barua
NOMBRESSwastika
APELLIDOBarua
FIRMABARUA S
AFILIACIONESTexas State University
ORCID0009-0008-4894-9131
VERIFICADOSí
TOTAL DE OBRAS4
TOTAL DE CITAS0
OBRAS COMO AUTOR4
OBRAS COMO EDITOR0
PRIMER AÑO DE PUBLICACIÓN2025
AÑO MÁS RECIENTE DE PUBLICACIÓN2026
ÍNDICE H0
  • Explainable AI-driven hybrid modeling for crash severity analysis near bus stops in urban areas

    Open Access•Swastika Barua, Rohit Chakraborty et al.•ARTICLE•International Journal of Urban…•2026

    Crashes near bus stops in urban areas present critical safety risks for pedestrians and vehicle occupants, especially in high-traffic areas with frequent transit activity. This study investigates crash severity patterns near Texas bus stops from 2017 to 2023 using a hybrid explainable AI framework. XGBoost and Random Forest models were applied, as part of feature selection process, to identify key contributing factors, which were subsequently use…

  • Classifying crash severity by SAE automation level using transformer models

    Open Access•Mahmuda Sultana Mimi, Md Majharul Islam et al.•ARTICLE•Transport Policy•2026

  • Toward safer micromobility

    Open Access•Jinli Liu, Swastika Barua et al.•ARTICLE•Cities•2026

  • Built environment and injury risk

    Open Access•Syed Aaqib Javed, Swastika Barua et al.•ARTICLE•Cities•2025

Sin obras prominentes en esta página.

  • Built environment and injury risk

    Open Access•Syed Aaqib Javed, Swastika Barua et al.•ARTICLE•Cities•2025

  • Explainable AI-driven hybrid modeling for crash severity analysis near bus stops in urban areas

    Open Access•Swastika Barua, Rohit Chakraborty et al.•ARTICLE•International Journal of Urban…•2026

    Crashes near bus stops in urban areas present critical safety risks for pedestrians and vehicle occupants, especially in high-traffic areas with frequent transit activity. This study investigates crash severity patterns near Texas bus stops from 2017 to 2023 using a hybrid explainable AI framework. XGBoost and Random Forest models were applied, as part of feature selection process, to identify key contributing factors, which were subsequently use…

  • Classifying crash severity by SAE automation level using transformer models

    Open Access•Mahmuda Sultana Mimi, Md Majharul Islam et al.•ARTICLE•Transport Policy•2026

  • Toward safer micromobility

    Open Access•Jinli Liu, Swastika Barua et al.•ARTICLE•Cities•2026

Crash (4 obras) · Poison control (4 obras) · Traffic and Road Safety (4 obras) · Autonomous Vehicle Technology and Safety (2 obras) · Injury prevention (2 obras) · SAFER (2 obras) · Urban Transport and Accessibility (2 obras) · Assistive Technology in Communication and Mobility (1 obra) · Automation (1 obra) · Built environment (1 obra)

Ethnos_APP • Proyecto Open Source • Licencia MIT • Frontend v2.0.0 • Privacidad y Cookies • Documentación de la API: api.ethnos.app/docs • Código de la API: GitHub • DOI: 10.5281/zenodo.17049435 • Código del Frontend: GitHub • DOI: 10.5281/zenodo.17050053 • cruz.rio.br • Expectantes Misericordiae