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Assess Audit Risk Using a Data Mining Approach Based on Neural Networks in Companies Listed on The Tehran Stock Exchange
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Davood Hemmati   , Mehdi Arab salehi nasrabadi * , Abbas Toloee ashlaghi |
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Abstract: (528 Views) |
| Audit planning is associated with auditing risk assessment. The purpose of this study is to assess audit risk using a data mining approach Based on neural networks in companies listed on the Tehran Stock Exchange that has been during the years 2017 to 2019, based on data taken from 90 companies. EXCEL software has been used to sort the data and MATLAB software has been used to analyze the research findings and codify each of the algorithms used. To assess the audit risk, the strength of each model was assessed through the neural network dialog. First, in this study artificial neural network method was used and then combine it with a particle cluster optimization algorithm. Then, in order to compare the prediction results, the mean error percentage, mean absolute error value, squared mean square error and correlation coefficient were used. The results showed that the combined model has a higher predictive power. |
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| Keywords: Auditing Risk, Data Mining Approach, Artifical Neural Network |
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Full-Text [PDF 769 kb]
(282 Downloads)
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Type of Study: Research |
Subject:
Auditing
Received: 2021/12/10 | Accepted: 2022/03/12 | Published: 2022/12/31
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