این سایت در حال حاضر پشتیبانی نمی شود و امکان دارد داده های نشریات بروز نباشند
Iranian Journal of Numerical Analysis and Optimization، جلد ۱۴، شماره Issue ۴، صفحات ۱۰۳۷-۱۰۶۸
عنوان فارسی
چکیده فارسی مقاله
کلیدواژه‌های فارسی مقاله
عنوان انگلیسی A space-time least-squares support vector regression scheme for inverse source problem of the time-fractional wave equation
چکیده انگلیسی مقاله The inverse problems in various fields of applied sciences and industrial design are concerned with the estimation of parameters that cannot be directly measured. In this work, we present a novel numerical approach for addressing the fractional inverse source problem by a machine learning algorithm and considering the ideas behind the spectral methods. The introduced algorithm utilizes a space-time Galerkin type of least-squares support vector regression (LS-SVR) to approximate the unknown source in a finite-dimensional space, providing a stable and efficient solution. With the proposed machine learning method, we overcome the limitations of classical numerical methods and offer a promising alternative for tackling inverse source problems while avoiding overfitting by carefully selecting regularization parameters. To validate the effectiveness of our approach and illustrate an exponential convergence, we present some test problems along with the corresponding numerical results. The proposed method's superior accuracy compared to the existing methods is also illustrated.
کلیدواژه‌های انگلیسی مقاله Machine learning,Support Vector Machines,Inverse source problem,Time fractional wave equation,Space-time Galerkin
نویسندگان مقاله Abumoslem Mohammadi |
Department of Mathematics, Shahed University, Tehran, Iran.

Abolfazl Tari Marzabad |
Department of Mathematics, Shahed University, Tehran, Iran.

نشانی اینترنتی https://ijnao.um.ac.ir/article_45349_2601aae85fb9232901031fc13bfae522.pdf
فایل مقاله فایلی برای مقاله ذخیره نشده است
کد مقاله (doi)
زبان مقاله منتشر شده en
موضوعات مقاله منتشر شده
نوع مقاله منتشر شده
برگشت به: صفحه اول پایگاه   |   نسخه مرتبط   |   نشریه مرتبط   |   فهرست نشریات