Электронный каталог

Статья

Ayriyan, A.
Sampling of Integrand for Integration Using Shallow Neural Network / A.Ayriyan, H.Grigorian, V.Papoyan // Discrete and Continuous Models and Applied Computational Science [Electronic resource]. – 2024. – Vol. 32, No. 1. – P. 38-47. – URL: https://journals.rudn.ru/miph/article/view/40098/23708. – Bibliogr.: 12.

In this paper, we study the effect of using the Metropolis–Hastings algorithm for sampling the integrando n the accuracy of calculating the value of the integral with the use of shallow neural network. In addition, a hybrid method for sampling the integrand is proposed, in which part of the training sample is generated by applying the Metropolis–Hastings algorithm, and the other part includes points of a uniform grid. Numerical experiments show that when integrating in high-dimensional domains, sampling of integrands both by the Metropolis–Hastings algorithm and by a hybrid method is more efficient with respect to the use of a uniform grid.



ОИЯИ = ОИЯИ (JINR)2024
Спец.(статьи,препринты) = С 325.1а - Нейронные сети и клеточные автоматы
Бюллетени = 47/024