The authors propose a learning method for fuzzy inference rules by a descent method. From
input-output data gathered from specialists, the inference rules expressing the input-output …

Over the last decade or so, significant advances have been made in two distinct
technological areas: fuzzy logic and computational neutral networks. The theory of fuzzy …

The advent of the computer age has set in motion a profound shift in our perception of
science-its structure, its aims and its evolution. Traditionally, the principal domains of …

Thispaperdescribesthetrendand researchdirectionsforfuturedevelopmentofte… logic.
Followingtobackground, section2 describes twopossiblefusingmethods. Oneofwhichisa …

A new fuzzy controller is presented based on the single input rule modules (SIRMs)
dynamically connected fuzzy inference model for upswing and stabilization control of …

The unified approach to fuzzy modeling developed in this correspondence addresses the
problems of structure and parameter identification of fuzzy models. It demonstrates an …

In recent years, an increasing number of researchers have become involved in the subject of
fuzzy neural networks in the hope of combining the strengths of fuzzy logic and neural …

Whereas conventional fuzzy reasoning lacks determining membership functions, a neural
network driven fuzzy reasoning (NDF) capable of determining membership functions …

We first introduce notation in an attempt to standardize the description of a basic fuzzy
controller. If r 1, r 2,…, rn are the real number inputs to the fuzzy controller and δ is its …

Thispaperdescribeshowneuralnetworks andfuzzylogichave
beenappliedtoconsumerproducts. First, thebackgroundbehind whybothtechnologieshavebeenappliedtothi …