C3S2 – The Clarkson Center for Complex Systems Science

Professor Ying-Cheng Lai, Arizona State University

Will present a talk entitled:

How do you know you are in a transient? – Predicting collapse of dynamical systems with machine learning

Abstract: To predict a critical transition due to parameter drift without relying on model is an outstanding problem in nonlinear dynamics and applied fields. A closely related problem is to predict whether the system is already in or if the system will be in a transient state preceding its collapse. A model free, machine-learning solution to both problems through the development of a parameter-cognizant reservoir computing framework will be presented. When the machine is trained only with data from the normal functioning regime with a chaotic attractor (i.e., before the critical transition), the transition point can be predicted accurately. Remarkably, for a parameter drift through the critical point, the machine is able to predict not only that the system will be in a transient state, but also the average transient time before the final collapse. Applications to electrical power and ecological systems will be demonstrated. The machine- learning framework can also be extended to predicting synchronization transition and amplitude death in coupled nonlinear systems.

Bio: Ying-Cheng Lai is the ISS Endowed Professor of Electrical Engineering and a Professor of Physics at Arizona State University. He was a PECASE recipient in 1997 and has been a Fellow of the American Physical Society since 1999. In 2016, he was selected by the Pentagon for the Vannevar Bush Faculty Fellowship. In 2018, he was elected as a Foreign Member of National Academy of Science and Letters of Scotland. In 2020, he was elected as a Foreign Member of Academia Europaea (The Academy of Europe) and as a Fellow of AAAS.

Join Zoom Meeting
https://clarkson.zoom.us/j/98280404151?pwd=cE9UOW9JTjQ1bUdLWThkb2ROUGg3Zz09

Meeting ID: 982 8040 4151
Passcode: 219449
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Friday, April 2nd, 2021

2:10 pm

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C3S2 Clarkson Center for Complex Systems Science l  http://webspace.clarkson.edu/~ebollt/Website-C3S2/index.html

CLARKSON UNIVERSITY  l  Potsdam, New York 13699-5720

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