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AI Model Predicts Earthquake Risks for Tokyo's Urban Planning

8/10/2025

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Summary

Story summary

In a groundbreaking study, researchers at Japan's Shibaura Institute of Technology have harnessed machine learning to predict subsurface bearing stratum depth in earthquake-prone Tokyo. Analyzing 942 geological surveys, their random forest model achieved an impressive accuracy with a mean absolute error of just 0.86 meters, paving the way for smarter urban planning and improved disaster preparedness.

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Story summary

In a groundbreaking study, researchers at Japan's Shibaura Institute of Technology have harnessed machine learning to predict subsurface bearing stratum depth in earthquake-prone Tokyo. Analyzing 942 geological surveys, their random forest model achieved an impressive accuracy with a mean absolute error of just 0.86 meters, paving the way for smarter urban planning and improved disaster preparedness.