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Going Concern Prediction of Iranian Companies by Using Fuzzy C-Means

نویسنده:
مهدی مرادی
,
مهدی صالحی
,
هادی صدوقی یزدی
,
Mohammad Ebrahim Gorgani
,
Mahdi Moradi
,
Mahdi Salehi
,
Hadi Sadoghi Yazdi
سال
: 2012
چکیده: Decision-making problems in the area of financial status evaluation have been considered very important. Making in- correct decisions in firms is very likely to cause financial crises and distress. Predicting going concern of factories and manufacturing companies is the desire of managers, investors, auditors, financial analysts, governmental officials, employees. This research introduces a new approach for modeling of company’s behavior based on Fuzzy Clustering Means (FCM). Fuzzy clustering is one of well-known unsupervised clustering techniques, which allows one piece of data belongs to two or more clusters. The data used in this research was obtained from Iran Stock Market and Account ing Research Database. According to the data between 2000 and 2009, 70 pairs of companies listed in Tehran Stock Exchange are selected as initial data set. Our experimental results showed that FCM approach obtains good prediction accuracy in developing a financial distress prediction model. Also, in effective features determination test the results show that features based on cash flows play more important role in clustering two classes.
یو آر آی: https://libsearch.um.ac.ir:443/fum/handle/fum/3344209
کلیدواژه(گان): Going Concern Prediction,Fuzzy C-Means
کالکشن :
  • ProfDoc
  • نمایش متادیتا پنهان کردن متادیتا
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    Going Concern Prediction of Iranian Companies by Using Fuzzy C-Means

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contributor authorمهدی مرادیen
contributor authorمهدی صالحیen
contributor authorهادی صدوقی یزدیen
contributor authorMohammad Ebrahim Gorganien
contributor authorMahdi Moradifa
contributor authorMahdi Salehifa
contributor authorHadi Sadoghi Yazdifa
date accessioned2020-06-06T13:09:57Z
date available2020-06-06T13:09:57Z
date issued2012
identifier urihttps://libsearch.um.ac.ir:443/fum/handle/fum/3344209
description abstractDecision-making problems in the area of financial status evaluation have been considered very important. Making in- correct decisions in firms is very likely to cause financial crises and distress. Predicting going concern of factories and manufacturing companies is the desire of managers, investors, auditors, financial analysts, governmental officials, employees. This research introduces a new approach for modeling of company’s behavior based on Fuzzy Clustering Means (FCM). Fuzzy clustering is one of well-known unsupervised clustering techniques, which allows one piece of data belongs to two or more clusters. The data used in this research was obtained from Iran Stock Market and Account ing Research Database. According to the data between 2000 and 2009, 70 pairs of companies listed in Tehran Stock Exchange are selected as initial data set. Our experimental results showed that FCM approach obtains good prediction accuracy in developing a financial distress prediction model. Also, in effective features determination test the results show that features based on cash flows play more important role in clustering two classes.en
languageEnglish
titleGoing Concern Prediction of Iranian Companies by Using Fuzzy C-Meansen
typeJournal Paper
contenttypeExternal Fulltext
subject keywordsGoing Concern Predictionen
subject keywordsFuzzy C-Meansen
journal titleOpen Journal of Accountingfa
pages38-46
journal volume1
journal issue2
identifier linkhttps://profdoc.um.ac.ir/paper-abstract-1030642.html
identifier articleid1030642
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