document: Hierarchical neuro-fuzzy quadtree models Hybrid neuro-fuzzy systems have been in evidence during the past few years , due to its attractive combination of the learning capacity of artificial neural networks with the interpretability of the fuzzy systems . This article proposes a new hybrid neuro-fuzzy model , named hierarchical neuro-fuzzy quadtree -LRB- HNFQ -RRB- , which is based on a recursive partitioning method of the input space named quadtree . The article describes the architecture of this new model , presenting its basic cell and its learning algorithm . The HNFQ system is evaluated in three well known benchmark applications : the sinc -LRB- x , y -RRB- function approximation , the Mackey Glass chaotic series forecast and the two spirals problem . When compared to other neuro-fuzzy systems , the HNFQ exhibits competing results , with two major advantages it automatically creates its own structure and it is not limited to few input variables
doc_bio_tags: O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O B O O O O O O O O O B I O O O O O O B O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O B I I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O
extractive_keyphrases: fuzzy systems quadtree recursive partitioning learning algorithm mackey glass chaotic series
abstractive_keyphrases: neuro-fuzzy systems hierarchical neuro-fuzzy quadtree