TY - JOUR
T1 - Legendre Neural Network for Solving Linear Variable Coefficients Delay Differential-Algebraic Equations with Weak Discontinuities
AU - Liu , Hongliang
AU - Song , Jingwen
AU - Liu , Huini
AU - Xu , Jie
AU - Li , Lijuan
JO - Advances in Applied Mathematics and Mechanics
VL - 1
SP - 101
EP - 118
PY - 2020
DA - 2020/10
SN - 13
DO - http://doi.org/10.4208/aamm.OA-2019-0281
UR - https://global-sci.org/intro/article_detail/aamm/18342.html
KW - Convergence, delay differential-algebraic equations, Legendre activation function, neural network.
AB - <p style="text-align: justify;">In this paper, we propose a novel Legendre neural network combined with the extreme learning machine algorithm to solve variable coefficients linear delay differential-algebraic equations with weak discontinuities. First, the solution interval is divided into multiple subintervals by weak discontinuity points. Then, Legendre neural network is used to eliminate the&nbsp; hidden layer by expanding the input pattern using Legendre polynomials on each subinterval. Finally, the parameters of the neural network are obtained by training with the extreme learning machine. The numerical examples show that the proposed method can effectively deal with the difficulty of numerical simulation caused by the discontinuities.</p>