Neural-Network Methods for Boundary Value Problems with Irregular Boundaries  

Oleh:

Likas, A. C. ; Lagaris, I. E. ; Papageorgiou, D. G.

Jenis: Article from Journal - ilmiah internasional
Dalam koleksi: IEEE Transactions on Neural Networks vol. 11 no. 5 (2000), page 1041-1049.
Topik: boundaries; neural - network; methods; boundary value problems; irregular

Ketersediaan

Perpustakaan Pusat (Semanggi) Nomor Panggil: II36.4 Non-tandon: 1 (dapat dipinjam: 0) Tandon: tidak ada

Lihat Detail Induk

Isi artikel

Partial differential equations (PDE s) with boundary conditions (Dirichlet or Neumann) defined on boundaries with simple geometry have been successfully treated using sigmoidal multilayer perceptrons in previous works. The article deals with the case of complex boundary geometry, where the boundary is determined by a number of points that belong to it and are closely located, so as to offer a reasonable representation. Two networks are employed : a multilayer perceptron and a radial basis function network. The later is used to account for the exact satisfaction of the boundary conditions. The method has been successfully tested on two - dimensional and three - dimensional PDEs and has yielded accurate results.

Opini Anda

Klik untuk menuliskan opini Anda tentang koleksi ini!

Kembali