Fuzzy Boolean Networks Learning Behaviour
J.A.B. Tome, João Paulo Carvalho · Seventh International Conference on Intelligent Systems Design and Applications (ISDA 2007) · 2007
In this paper one studies the learning behaviour of an entire rule base in fuzzy Boolean networks. It is analyzed the influence of a set of factors such as number of inputs per neuron, granularity of antecedent spaces and number of teaching experiments on learning effectiveness without cross influence between rules and on interpolation capabilities of the network. Both one dimensional problems and two dimensional problems are tested and results interpreted using theoretical results also presented.