eprintid: 2358
rev_number: 6
eprint_status: archive
userid: 507
dir: disk0/00/00/23/58
datestamp: 2012-07-20 05:56:17
lastmod: 2012-07-20 05:56:17
status_changed: 2012-07-20 05:56:17
type: article
metadata_visibility: show
creators_name: Abadi, Agus Maman
creators_name: Subanar, 
creators_name: Widodo, -
creators_name: Saleh, Samsubar
creators_id: agusmaman@uny.ac.id
creators_id: subanar@yahoo.com
creators_id: widodo_math@yahoo.com
creators_id: 4humas@paue.ugm.ac.id <4humas@paue.ugm.ac.id
title: CONSTRUCTING COMPLETE FUZZY RULES OF FUZZY MODEL USING SINGULAR VALUE DECOMPOSITION
subjects: F4
full_text_status: none
abstract: In the fuzzy model, there are many ways to design fuzzy rules from input-output data. Those are gradient descent training, table lookup scheme, recursive least squares and clustering. The aim in this paper is to construct complete fuzzy rules from input-output data using singular value decomposition. Designing fuzzy rules by singular value decomposition is based on minimizing the square of residual between overall output of the real system and identified model. Thus, the designed fuzzy rules are used to construct fuzzy model by choosing fuzzifier, defuzzifier and inference engine. Furthermore, the fuzzy model is applied to predict inflation rate in Indonesia. Key words: fuzzy rules, fuzzy model, singular value decomposition.
date: 2011
date_type: submitted
citation:   Abadi, Agus Maman and Subanar and Widodo, - and Saleh, Samsubar  (2011) CONSTRUCTING COMPLETE FUZZY RULES OF FUZZY MODEL USING SINGULAR VALUE DECOMPOSITION.