The role of Dataset in training ANFIS System for Course Advisor
V.Vaidhehi. International Journal of Innovative Research in Advanced Engineering, 1 (6):
249-253(July 2014)
Abstract
Adaptive Network based Fuzzy Inference System (ANFIS) is used in the field of decision making to help the students to choose the best course according to his/her requirements. The structure of ANFIS system and the datasets used to train the system play a vital role in evaluating the performance of the system. This paper is based on the design of Sugeno type ANFIS with grid partitioning and the usage of different datasets to train the system using MATLAB. Results demonstrate that proper dataset is needed for training the ANFIS model
%0 Journal Article
%1 vvaidhehi2014dataset
%A V.Vaidhehi,
%D 2014
%E IJIRAE,
%J International Journal of Innovative Research in Advanced Engineering
%K ANFIS MATLAB Sugeno advisor course dataset fuzzy grid neuro partitioning system
%N 6
%P 249-253
%T The role of Dataset in training ANFIS System for Course Advisor
%U http://www.ijirae.com/images/downloads/vol1issue6/JYCS10114(38).25.pdf
%V 1
%X Adaptive Network based Fuzzy Inference System (ANFIS) is used in the field of decision making to help the students to choose the best course according to his/her requirements. The structure of ANFIS system and the datasets used to train the system play a vital role in evaluating the performance of the system. This paper is based on the design of Sugeno type ANFIS with grid partitioning and the usage of different datasets to train the system using MATLAB. Results demonstrate that proper dataset is needed for training the ANFIS model
@article{vvaidhehi2014dataset,
abstract = {Adaptive Network based Fuzzy Inference System (ANFIS) is used in the field of decision making to help the students to choose the best course according to his/her requirements. The structure of ANFIS system and the datasets used to train the system play a vital role in evaluating the performance of the system. This paper is based on the design of Sugeno type ANFIS with grid partitioning and the usage of different datasets to train the system using MATLAB. Results demonstrate that proper dataset is needed for training the ANFIS model },
added-at = {2014-08-06T04:37:17.000+0200},
author = {V.Vaidhehi},
biburl = {https://www.bibsonomy.org/bibtex/2a531ff29f05c7c80572068c0a4544acc/ijirae_journal},
editor = {IJIRAE},
interhash = {822a87c222080b49f6aa9312339d8b80},
intrahash = {a531ff29f05c7c80572068c0a4544acc},
journal = {International Journal of Innovative Research in Advanced Engineering},
keywords = {ANFIS MATLAB Sugeno advisor course dataset fuzzy grid neuro partitioning system},
month = {july},
number = 6,
pages = {249-253},
timestamp = {2014-08-06T04:37:17.000+0200},
title = {The role of Dataset in training ANFIS System for Course Advisor},
url = {http://www.ijirae.com/images/downloads/vol1issue6/JYCS10114(38).25.pdf},
volume = 1,
year = 2014
}