An application of a neuro-fuzzy inference system for pattern classification of HDD defect distribution

Author

Moon, Un-Chul ; Jang, Hoyoun ; Santos, Marcus Vinicius dos

Author_Institution

Sch. of Electr. & Electron. Eng., Chung-Ang Univ., Seoul, South Korea

fYear

2010

fDate

12-14 July 2010

Firstpage

1

Lastpage

5

Abstract

In the production of Hard Disk Drive (HDD), the pattern of HDD defect distribution gives the information about the defective component of HDD. This paper presents a pattern classification method for the HDD defect distribution. Five features of the pattern are developed and an Adaptive Neuro-Fuzzy Inference System (ANFIS) is applied to classify the input pattern. The ANFIS is trained with the sense of supervised learning. The trained ANFIS shows satisfactory results for classification of HDD defect distribution.

Keywords

disc drives; fuzzy neural nets; fuzzy reasoning; hard discs; pattern classification; production engineering computing; ANFIS; HDD defect distribution; adaptive neuro-fuzzy inference system; defective component; hard disk drive; pattern classification; Adaptive systems; Fuzzy logic; Hard disks; Neural networks; Pattern classification; Pattern recognition; Performance evaluation; Testing; Training data; Watches; Adpative Neuro-Fuzzy Inference System(ANFIS); Hard Disk Drive(HDD); Pattern Classification; component;

fLanguage

English

Publisher

ieee

Conference_Titel

Fuzzy Information Processing Society (NAFIPS), 2010 Annual Meeting of the North American

Conference_Location

Toronto, ON

Print_ISBN

978-1-4244-7859-0

Electronic_ISBN

978-1-4244-7857-6

Type

conf

DOI

10.1109/NAFIPS.2010.5548200

Filename

5548200