Predicting phase transitions

I am not sure the modelling methodology described in this article is quite as good as the title suggests…

“Chaos Researchers Can Now Predict Perilous Points of No Return”

… but it would be very interesting if it lives up to the claims made in the article. It is a quick read and the subject matter seems worth keeping an eye on.

Here are two short extracts to give you a flavour of the claims made

A custom-built machine learning algorithm can predict when a complex system is about to switch to a wildly different mode of behavior.

In a series of recent papers, researchers have shown that machine learning algorithms can predict tipping-point transitions in archetypal examples of such “nonstationary” systems, as well as features of their behavior after they’ve tipped. The surprisingly powerful new techniques could one day find applications in climate science, ecology, epidemiology and many other fields.

Tony – From the Outside

Author: From the Outside

After working in the Australian banking system for close to four decades, I am taking some time out to write and reflect on what I have learned. My primary area of expertise is bank capital management but this blog aims to offer a bank insider's outside perspective on banking, capital, economics, finance and risk.

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