Titlebook: Civil Engineering for Multi-Hazard Risk Reduction; Select Proceedings o K. S. Sreekeshava,Sreevalsa Kolathayar,N. Vinod Ch Conference proce

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2366-2557 , disaster resilient infrastructure, nano-composites and bio-composites, sustainable geotechnics and earthquake engineering. This book serves as a resource material for researchers and industry professionals interested in disaster risk reduction..978-981-99-9612-4978-981-99-9610-0Series ISSN 2366-2557 Series E-ISSN 2366-2565

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https://doi.org/10.1057/9781137031716le Regression is 0.792 for original data, 0.803 for 150 random data, and 0.801 for 300 random data. However, at other locations, the suitability of a particular regression model can be determined and recommended.

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Prediction of Noise Pollution of Delhi City Using Machine Learning: A Case Studyle Regression is 0.792 for original data, 0.803 for 150 random data, and 0.801 for 300 random data. However, at other locations, the suitability of a particular regression model can be determined and recommended.

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Event-Based Sensing for Improved Traffic Detection and Tracking in Intelligent Transport Systems Townential-decay time surface analysis, which provide valuable visual insights. By effectively utilizing event-based sensing and incorporating innovative techniques, this research contributes to the advancement of vision-based traffic monitoring for sustainable mobility within the field of Intelligent Transport Systems.

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