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http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/8399
Title: | 利用深度學習預測審計失敗--以台灣為例 Predict Audit Failure Using Deep Learning Algorithm—Take Taiwan as Example |
Authors: | Chia-Yang Hsu 徐佳揚 |
Advisor: | 吳琮璠(Chung-Fern Wu) |
Keyword: | 會計師,審計失敗,深度學習,機器學習, Auditor,Audit Failure,Deep Learning,Machine Learning, |
Publication Year : | 2021 |
Degree: | 碩士 |
Abstract: | 利用台灣上市、櫃公司財務報表重編作為審計失敗的指標,並依照Fully Connected Feedforward Network架構架設深度學習模型,用以預測可能發生審計失敗的查核案件,並利用半監督式學習與Voting等方式強化預測效果。與對照組邏輯斯回歸模型相比,預測能力顯著提升。 Used financial statement restatements of Taiwanese lised companies as indicator of audit failure, and built a Deep learning models based on Fully Connected Feedforward Network framework to predict audit failure, then used semi-supervised learning and Noting methods to improve prediction outcome. The predictive ability was signigicantly improved compared with the logistic regression model of the control group. |
URI: | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/8399 |
DOI: | 10.6342/NTU202100827 |
Fulltext Rights: | 同意授權(全球公開) |
Appears in Collections: | 會計學系 |
Files in This Item:
File | Size | Format | |
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U0001-1204202115134100.pdf | 2.77 MB | Adobe PDF | View/Open |
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