The Conference on Modern Management Sciences , 2012-07-27

Title : ( Management Assessment of Going Concern Based on Data Mining Using Adaptive Network Based Fuzzy Inference Systems (ANFIS) )

Authors: Fezeh Zahedi Fard , Mahdi Salehi ,

Citation: BibTeX | EndNote

Going concern is a fundamental concept for the preparation of financial statements by management. This paper has employed a data mining approach for going concern prediction (GCP) and has applied Adaptive Network Based Fuzzy Inference Systems (ANFIS) based on feature selection method for GCP in Iranian firms, listed in Tehran Stock Exchange (TSE). For this purpose, at the first step, using the stepwise discriminant analysis (SDA) has opted the final variables from among of 42 variables and in the next stage, has applied 10-fold cross validation to figure out the optimal model for one year ahead. The empirical test signifies that the ANFIS model reached 99.92 and 95.19 percent accuracy rates so as to train and hold-out data.

Keywords

ANFIS; data mining; feature selection; financial ratios; going concern
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@inproceedings{paperid:1029726,
author = {Fezeh Zahedi Fard and Salehi, Mahdi},
title = {Management Assessment of Going Concern Based on Data Mining Using Adaptive Network Based Fuzzy Inference Systems (ANFIS)},
booktitle = {The Conference on Modern Management Sciences},
year = {2012},
location = {IRAN},
keywords = {ANFIS; data mining; feature selection; financial ratios; going concern prediction},
}

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%0 Conference Proceedings
%T Management Assessment of Going Concern Based on Data Mining Using Adaptive Network Based Fuzzy Inference Systems (ANFIS)
%A Fezeh Zahedi Fard
%A Salehi, Mahdi
%J The Conference on Modern Management Sciences
%D 2012

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