Can machine learning predict chaotic systems?

Some of the most impressive and latest applications of Machine Learning for prediction in chaotic systems utilize Reservoir Computing (RC). RC is based on ideas behind RNNs. This framework does data-driven prediction of the evolution of a system’s state.

Are neural networks chaotic systems?

The use of artificial neural networks as models of chaotic dynamics has been rapidly expanding. These geometric operations indicate topological mixing and chaos, explaining why neural networks are naturally suitable to emulate chaotic dynamics.

How is chaos theory used in today’s world?

Take weather for example. Weather patterns are a perfect example of Chaos Theory. We can usually predict weather patterns pretty well when they are in the near future, but as time goes on, more factors influence the weather, and it becomes practically impossible to predict what will happen.

What is readout layer?

Readout. The readout is a neural network layer that performs a linear transformation on the output of the reservoir.

Can a machine-learning algorithm learn chaos?

The findings come from veteran chaos theorist Edward Ott and four collaborators at the University of Maryland. They employed a machine-learning algorithm called reservoir computing to “learn” the dynamics of an archetypal chaotic system called the Kuramoto-Sivashinsky equation.

Can machine learning predict the future of chaotic systems?

In a series of results reported in the journals Physical Review Letters and Chaos, scientists have used machine learning — the same computational technique behind recent successes in artificial intelligence — to predict the future evolution of chaotic systems out to stunningly distant horizons.

What is machine learning and why is it so powerful?

The machine-learning technique is almost as good as knowing the truth. That’s why machine learning is “a very useful and powerful approach,” said Ulrich Parlitz of the Max Planck Institute for Dynamics and Self-Organization in Göttingen, Germany, who, like Jaeger, also applied machine learning to low-dimensional chaotic systems in the early 2000s.

Can machine-learning help us predict the weather?

Besides weather forecasting, experts say the machine-learning technique could help with monitoring cardiac arrhythmias for signs of impending heart attacks and monitoring neuronal firing patterns in the brain for signs of neuron spikes.