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April 1, 2026Proceedings of the Institution of Mechanical Engineers Part D Journal of Automobile Engineering

Integrated dynamic analysis and predictive modeling of sustainable vehicular transport using a hybrid system dynamics-machine learning method

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Authors

APArpan PaulSMSudipta Mahapatra

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Overview

Quantitative modeling predicts transportation outcomes in sustainability, indicating key input factors.

Key Points

  • The aim is to develop a sustainable transportation model that predicts system adaptability using dynamic factors.
  • Developed a system dynamics model to visualize dynamic factors affecting sustainability.
  • Employed ensemble learning with four machine learning algorithms for accurate predictions.
  • Conducted Sobol sensitivity analysis to examine input-output relationships.
  • Performed five quantitative scenario analyses to assess future system states under uncertainty.
  • Identified fuel price, vehicle speed, and product demand as crucial input parameters.
  • Observed significant fluctuations in transportation costs as an output of the model.

Cite This Study

Paul et al. (2026) studied this question.

synapsesocial.com/papers/69cd7a915652765b073a7c7bhttps://doi.org/10.1177/09544070261434415
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