PL EN


Preferencje help
Widoczny [Schowaj] Abstrakt
Liczba wyników
Tytuł artykułu

A fuzzy neural network for knowledge acquisition in complex time series

Autorzy
Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
A novel fuzzy neural network, called FuNN, is applied here for time-series modeling. FuNN models have several features that make them well suited to a wide range of knowledge engineering applications. These strengths include fast and accurate learning, good generalisation capabilities, excellent explanation facilities in the form of semantically meaningful fuzzy rules, and the ability to accomodate both numerical data and existing expert knowledge about the problem under consideration. We investigate the effectiveness of the proposed neuro-fuzzy hybrid architectures for manipulating the future behaviour of nonlinear dynamical systems and interpreting fuzzy if-then rules. A well-known example of Box and Jenkins is used as a benchmark time series in the proposed modelling approach and the other modelling approach. Finally, experimental results and comparisons with the other popular neuro-fuzzy inference system, namely Adaptive Network-based Fuzzy Inference System (ANFIS) are also presented.
Rocznik
Strony
593--611
Opis fizyczny
Bibliogr. 18 poz.,Rys., wykr.,
Twórcy
autor
autor
autor
Bibliografia
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BAT2-0001-0564
JavaScript jest wyłączony w Twojej przeglądarce internetowej. Włącz go, a następnie odśwież stronę, aby móc w pełni z niej korzystać.