Machine Learning-based GIS Model for 2D and 3D Vehicular Noise Modelling in a Data-scarce Environment

Center for Advanced Modelling and Geospatial Information Systems (CAMGIS), School of Civil and Environmental Engineering, Faculty of Engineering and Information Technology, University of Technology SydneyAustralia

Abdulkareem, Ahmed

Aldulaimi, Ahmed

Center for Advanced Modelling and Geospatial Information Systems (CAMGIS), School of Civil and Environmental Engineering, Faculty of Engineering and Information Technology, University of Technology SydneyAustralia

Gite, Shilpa

Computer Science and Information Technology Department, Symbiosis Institute of Technology, Symbiosis International (Deemed) UniversityPune, India

Symbiosis Centre of Applied AI (SCAAI), Symbiosis International (Deemed) UniversityPune, India

Alamri, Abdullah

Department of Geology and Geophysics, College of Science, King Saud UniversityRiyadh, Saudi Arabia

Mukhopadhyay, Subhas Chandra

School of Engineering, Macquarie UniversityAustralia

Language:: English

Publication timeframe:: 1 times per year
Journal Subjects:: Engineering, Introductions and Overviews, Engineering, other

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Machine Learning-based GIS Model for 2D and 3D Vehicular Noise Modelling in a Data-scarce Environment

Biswajeet Pradhan

Ahmed Abdulkareem

Ahmed Aldulaimi

Shilpa Gite

Abdullah Alamri

Subhas Chandra Mukhopadhyay

Article Category: Research Article

Published Online: Aug 06, 2024

Received: Jun 10, 2024

DOI: https://doi.org/10.2478/ijssis-2024-0022

Keywords2D noise model, 3D noise model, artificial neural network, random forest, support vector machine

© 2024 Biswajeet Pradhan et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Keywords
2D noise model, 3D noise model, artificial neural network, random forest, support vector machine