Identification of trash types and computation of trash content in ginned cotton using soft computing techniques

Author

Siddaiah, Murali ; Prasad, Nadipuram R. ; Lieberman, Michael A. ; Hughs, Sidney E.

Author_Institution

Klipsch Sch. of Electr. & Comput. Eng., New Mexico State Univ., Las Cruces, NM, USA

Volume

1

fYear

1999

fDate

1999

Firstpage

547

Abstract

This paper discusses the use of soft computing techniques such as Fuzzy Logic and Neural Network based approaches in the identification of various types of trash (non-lint material/foreign matter), and the computation of trash content in ginned cotton. Lint is the cotton fiber; non-lint or foreign matter is essentially everything other than lint. Trash content is the percentage of sample surface covered by non-lint particles. The effectiveness of a hybrid neurofuzzy structure, namely the Adaptive Network-Based Fuzzy Inference System (ANFIS) to classify trash types is compared with other techniques

Keywords

fuzzy logic; fuzzy neural nets; inference mechanisms; pattern classification; textile industry; adaptive network fuzzy inference system; cotton fiber; cotton ginning; foreign matter; fuzzy logic; hybrid neurofuzzy structure; lint; neural network; nonlint material; soft computing; trash content; trash type classification; Adaptive systems; Computer networks; Cotton; Fuzzy logic; Fuzzy neural networks; Fuzzy systems; Laboratories; Neural networks; Textile industry; US Department of Agriculture;

fLanguage

English

Publisher

ieee

Conference_Titel

Circuits and Systems, 1999. 42nd Midwest Symposium on

Conference_Location

Las Cruces, NM

Print_ISBN

0-7803-5491-5

Type

conf

DOI

10.1109/MWSCAS.1999.867325

Filename

867325