𝔖 Bobbio Scriptorium
✦   LIBER   ✦

On the role of context in hierarchical fuzzy controllers

✍ Scribed by Luis Magdalena


Publisher
John Wiley and Sons
Year
2002
Tongue
English
Weight
480 KB
Volume
17
Category
Article
ISSN
0884-8173

No coin nor oath required. For personal study only.

✦ Synopsis


This article analyzes the role of context in hierarchical fuzzy controllers based on the decomposition of the input space. The usual consideration in most hierarchical fuzzy systems is the reduction of dimensionality problems. This article will analyze how to profit from the qualities of context as a key question in the definition of a fuzzy controller, to reduce the design efforts by making it easier to introduce the expert knowledge in that process. The idea is to use the output of a level of the hierarchy as the method to define (or adjust) the normalization functions (considered as contextual information) applied to the variables of the following level of that hierarchy.

Two different situations will be analyzed, including an application example for each case. In the first case the decomposition will affect variables placed at the same level of description (abstraction) regarding the problem to be solved. In the second case, the decomposition process works on variables placed at different levels of description of the problem (descriptions with a different level of abstraction).


πŸ“œ SIMILAR VOLUMES


Granular computing in the development of
✍ Witold Pedrycz; George Vukovich πŸ“‚ Article πŸ“… 1999 πŸ› John Wiley and Sons 🌐 English βš– 535 KB

This study elaborates on the role of information granularity in the development of fuzzy controllers. As opposed to numeric data being commonly accepted by fuzzy controllers, we discuss a general processing framework involving data-information granules exhibiting various levels of information granul

On the design of neural-fuzzy control sy
✍ Devinder Kaur; Bin Lin πŸ“‚ Article πŸ“… 1998 πŸ› John Wiley and Sons 🌐 English βš– 341 KB πŸ‘ 2 views

This article presents a neural᎐network-based fuzzy logic control NN᎐FLC system. The NN᎐FLC model has the learning capabilities for constructing membership functions and extracting fuzzy rules from training examples. Both unsupervised and supervised training algorithms are used to find the membership

Round table discussion on the estimation
✍ Madan M Gupta πŸ“‚ Article πŸ“… 1975 πŸ› Elsevier Science 🌐 English βš– 497 KB

## Rapport IFAC. Discussion autour d'une Table, sur l'Estimation et le Contr61e dans un Environnement Flou IFAC Bericht: Rundtischgespr~ich fiber die Schfitzung und Steuerung in unscharfer Umgebung OTqeT H~AK o/mcByccrm 3a rpyrm,mf Cq'OJIOM 06 o~eHxe H ynpaBY[eHHH ]3 paaMI, ITI, IX cpe~ax MADAN Su

Design of the fuzzy multiobjective contr
✍ Hwan-Chun Myung; Z. Zenn Bien πŸ“‚ Article πŸ“… 2003 πŸ› John Wiley and Sons 🌐 English βš– 319 KB

A multiobjective control problem has been handled in many different ways such as fuzzy, neural network and reinforcement learning, etc. Among them, a reinforcement learning method solves a multiobjective control problem without any prior knowledge. In this article, a new reinforcement learning metho

The role of context in search: Examining
✍ Elaine G. Toms; Luanne Freund; Joan C. Bartlett; Rick Kopak πŸ“‚ Article πŸ“… 2005 πŸ› Wiley (John Wiley & Sons) 🌐 English βš– 201 KB

## Abstract Using a 48‐person group in a within‐subjects design, we investigated how people search differently within diverse domains: consumer health, shopping, travel and general research. Our goal was to identify the distinctive characteristics of search behavior within each domain that impact t