Back to Results
First PageMeta Content
Fuzzy control system / Genetic fuzzy systems / Rough set / Fuzzy set / Membership function / Inference / Type-2 fuzzy sets and systems / Neuro-fuzzy / Logic / Fuzzy logic / Mathematical logic


A Framework of Adaptive T-S type Rough-Fuzzy Inference Systems (ARFIS) Chang Su Lee B.S. Electronic Engineering
Add to Reading List

Document Date: 2009-07-21 00:22:11


Open Document

File Size: 3,49 MB

Share Result on Facebook

City

Perth / /

Company

Control Systems Laboratory / General T-S Fuzzy Systems / Boeing / Automation Laboratory / Rough-Fuzzy Inference Systems / MISO T-S Fuzzy Systems / MIT Media Labs / /

Country

Australia / Korea / /

Facility

The University of Western Australia School / Control Systems Laboratory / /

IndustryTerm

sisters-in-law / inference systems / hybrid fuzzy systems / non-linear systems / fuzzy systems / statistical function-combined fuzzy systems / neural networks / genetic fuzzy systems / risk management / information processing systems / fuzzy inference systems / finance / conjugate gradient descent algorithm / /

Organization

University of Western Australia School of Electrical / Electronic and Computer Engineering / MIT / Computer Science Department / /

Person

Martin Masek / Guilhereme DeSouza / Joshua Young-Min Lee / James Ng / Adrian Boeing / Gary Bundell / Jesus Christ / Anthony Zaknich / Sung-Joo Lee / Thomas Bräunl / /

Position

Author / proposed rough-fuzzy controller / Professor / co-supervisor / lecturer / Fisher / representative / General / Head / Controller / previous Head / previous co-supervisor / /

ProvinceOrState

Wisconsin / /

Region

Western Australia / /

Technology

bioinformatics / hybridization / fuzzy logic / 6.16 The algorithm / conjugate gradient descent algorithm / /

SocialTag