Abstract
Extreme learning machine (ELM) algorithm, which becomes more and more popular in the area of artificial intelligence for the past few years, is faster than the traditional machine learning algorithms, especially than the single hidden layer feed-forward neural networks (SLFNs). However, ELM is merely commonly used in the field of computer science or other hot areas. This paper investigates the ability of ELM to emulate the atmospheric nonlinear systems. The performance of ELM on emulating the nonlinear chaotic system - Lorenz63 is analyzed. The results show that ELM can accurately and quickly simulate the Lorenz63 forecast field at different forecast length, and thus providing a new idea for solving kinds of atmospheric nonlinear equations.
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