A hybrid model through the fusion of type-2 fuzzy logic systems and extreme learning machines for modelling permeability prediction

摘要

The simplest computational models in artificial intelligence are so-called single hidden-layer feed-forward neural networks. These neural networks have to be trained, but the slow learning rate of simple algorithms makes this time-consuming. Extreme learning machines (ELMs) speed up this learning significantly, and they are much simpler to manage and require no tuning. The price to be paid is that ELMs are not capable of modeling uncertainties. But of course, the real-world data that is input to a training algorithm is full of uncertainties.