A novel inference algorithm for Active Learning Method

Author

Afrakoti, I.E.P. ; Shouraki, Saeed Bagheri ; Ghaffari, Aboozar

Author_Institution

Dept. of Electr. Eng., Sharif Univ. of Technol., Tehran, Iran

fYear

2013

fDate

6-8 March 2013

Firstpage

1

Lastpage

5

Abstract

This paper presents a new inference algorithm for Active Learning Method (ALM). ALM is a pattern-based algorithm for soft computing which uses the Ink Drop Spread (IDS) algorithm as its main engine for feature extraction. In this paper a fuzzy number is extracted from each IDS plane rather than the narrow path and spread as in previous approaches. In order to compare performance of the proposed algorithm with the original one, two functions which are widely used in literature are modeled as the benchmark. Simulation results show that the proposed algorithm is as effective as previous one in the modeling task.

Keywords

feature extraction; fuzzy set theory; inference mechanisms; learning (artificial intelligence); ALM; IDS algorithm; active learning method; feature extraction; fuzzy number; ink drop spread algorithm; novel inference algorithm; pattern-based algorithm; soft computing; Computational modeling; Feature extraction; Hardware; Inference algorithms; Ink; Input variables; Mathematical model; Active learning method (ALM); fuzzy inference algorithm; ink drop spread (IDS);

fLanguage

English

Publisher

ieee

Conference_Titel

Pattern Recognition and Image Analysis (PRIA), 2013 First Iranian Conference on

Conference_Location

Birjand

Print_ISBN

978-1-4673-6204-7

Type

conf

DOI

10.1109/PRIA.2013.6528436

Filename

6528436