دوره 31، شماره 58 - ( 1402 )
جلد 31 شماره 58 صفحات 164-131 |
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Moghri Gardroudbari M, Dadashi I, Mohseni Malek B I, Zabihi A. Predicting Tax Evasion of Legal Taxpayers with an Emphasis on Economic Components, Taxpayers and Auditors Characteristics;
Relying on Artificial Intelligence. J Tax Res 2023; 31 (58) :131-164
URL: http://taxjournal.ir/article-1-2312-fa.html
URL: http://taxjournal.ir/article-1-2312-fa.html
مقری گردرودباری محسن، داداشی ایمان، محسنی ملکی بهرام، ذبیحی علی. پیشبینی فرار مالیاتی مؤدیان حقوقی با تاکید بر مولفه‌های اقتصادی، مؤدیان و حسابرسان مالیاتی؛ با تکیه بر هوش مصنوعی. پژوهشنامه مالیات. 1402; 31 (58) :131-164
1- ، I.dadashi@qom.ac.ir
چکیده: (1509 مشاهده)
دولتها برای انجام وظایف عمومی خود نیاز به منابع مالی باثبات و مطمئن دارند و از دیرباز مالیات، یکی از مهمترین منابع تأمین مالی دولتها برای انجام وظایفشان بوده است. جلوگیری یا کاهش میزان فرار مالیاتی طی سالیان اخیر از دغدغههای مهم دولتها در عرصه اقتصادی بوده است. در این پژوهش مقوله فرار مالیاتی با استفاده از هوش مصنوعی و با تمرکز بر مجموعهای متشکل از 57 شاخص مالی و غیرمالی در سطح کلان اقتصادی، مؤدیان و حسابرسان مالیاتی، در نمونهای شامل 978 پرونده مؤدیان حقوقی اداره کل امور مالیاتی مازندران برای سالهای 1391 تا 1398 مورد بررسی قرار گرفته است. در این پژوهش به منظور استخراج ویژگیهای تاثیرگذار، از الگوریتمهای بهینهسازی سینوس کسینوس و گرگ خاکستری و جهت مدلسازی فرار مالیاتی و آزمون ویژگیها، از الگوریتمهای درخت تصمیم و شبکه عصبی مصنوعی استفاده شده است. براساس نتایج حاصله، الگوریتم بهینهسازی سینوس کسینوس به همراه پیشبینیکننده درخت تصمیم، مقدار خطای کمتری را نسبت به سایر مدلها دارا بوده و مدلی دقیقتر جهت پیشبینی فرار مالیاتی ارائه میدهد.
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