Model-Tree Ensembles for noise-tolerant system identification ?
We introduce a novel method for modeling dynamic systems. Comparable predictive performance to identification methods from control engineering. Output error evaluation on realistic process engineering case studies. Output error results show noise resilience even with up to 20% of noise added.
decision tree ensemble fuzzified model tree nonlinear dynamic system identification