چاپ کتاب دکتر قاسمی و همکارات در انتشارات بین المللی لمبرت(۲۰۱۸)

چاپ کتاب دکتر قاسمی و همکارات در انتشارات بین المللی لمبرت(۲۰۱۸)

Initially, financial failure and then the consequent distress of a business is an
costly and disturbing event. Actually, financial distress prediction models attempt to
forecast whether a business will experience financial distress in the future. investors
need to assess and analyze the financial statement, to make the logical decision. Using
financial ratios is one of the most common methods. The main purpose of this research
is to predict the financial distress, using ratios of liquidity. Four models, such as
Support vector machine, neural network back propagation, Decision tree and Adaptive
Neuro-Fuzzy Inference System had been compared. Furthermore, the ratios of liquidity
considered in a period of 2011_2015, so, the research method is qualitative and
quantitative and type of casual comparative. The result indicates that, the accuracy of
the neural network, Decision tree, and Adaptive Neuro-Fuzzy Inference System
illustrates that there is a significant differently 0/000 and 0/005 years this is more than
support vector machine result. Therefore, the result of support vector machine provides
that there is a significant differently 0/001 in years. In addition, this has been shown
that neural network in 2 years before the bankruptcy has the ability to predict a right
thing. Therefore, the results have been shown that all four models were statistically
significant. Consequently, there are no significant differences. All models have the
precision to predict the financial crisis.
Keywords: Financial crisis, Neural network, Decision tree, Adaptive Neuro-Fuzzy
Inference System, Support vector machine