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November 18, 2019 | 1:30 p.m. - 2:30 p.m.
Category: Lecture
Location: Faculty/Administration #1140 | Map
656 W. Kirby
Detroit, MI 48202
Cost: Free

Speaker: Professor Sourav Das, James Cook University - Cairns, Australia

Title: A Statistical Learning Algorithm for Tracking the Evolution of a Landslide

 

Abstract: This study builds on fundamental knowledge of granular failure dynamics to develop a statistical and machine learning approach for characterization of a landslide. We demonstrate our approach for a rockslide using surface displacement data from a ground-based radar monitoring  system. The algorithm has three key components:(i) identification of a regime change point t0 marking the departure from statistical invariance of the global velocity field, (ii) characterization of the clustering pattern formed by the velocity time series at t0, and (iii) classification of velocity patterns for t > t0 to deliver a measure of risk of failure from t0 and estimates of the time of emergent and imminent risk of failure. Unlike the prevailing approach of analyzing time series data from one or a few chosen locations, we make full use of data from all monitored points on the slope (here 1803). We do not make prior assumptions on the monitored domain and base our characterization of the complex spatial patterns and associated dynamics only from the data. Our approach is informed by recent developments in the physics and micromechanics of failure in granular media and is configured to readily accommodate additional data on landslide triggers and other determinants of landslide risk.

For more information about this event, please contact Department of Mathematics at 313-577-2479 or math@wayne.edu.