Hybrid forecasting of chaotic processes: Using machine learning in conjunction with a knowledge-based model
Hybrid forecasting of chaotic processes: Using machine learning in conjunction with a knowledge-based model
A model-based approach to forecasting chaotic dynamical systems utilizes knowledge of the mechanistic processes governing the dynamics to build an approximate mathematical model of the system. In contrast, machine learning techniques have demonstrated promising results for forecasting chaotic systems purely from past time series measurements of system state variables (training …