An efficient algorithm based on artificial neural networks and particle swarm optimization for solution of nonlinear Troesch’s problem

Particle swarm optimisation for dynamic optimisation problems: a review

(2014) Ahmad Rezaee Jordehi   NEURAL COMPUTING & APPLICATIONS

Automated design parameter selection for neural networks solving coupled partial differential equations with discontinuities

(2012) Kevin Stanley McFall   JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS

Multilayer perceptrons and radial basis function neural network methods for the solution of differential equations: A survey

(2011) Manoj Kumar et al.   COMPUTERS & MATHEMATICS WITH APPLICATIONS

Troesch’s problem: A B-spline collocation approach

(2011) S.A. Khuri et al.   MATHEMATICAL AND COMPUTER MODELLING

The sinc–Galerkin method for solving Troesch’s problem

(2011) M. Zarebnia et al.   MATHEMATICAL AND COMPUTER MODELLING

A variational iteration method for solving Troesch’s problem

(2010) Shih-Hsiang Chang   JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS

Simplifying Particle Swarm Optimization

(2009) M.E.H. Pedersen et al.   APPLIED SOFT COMPUTING

Artificial Neural Network Method for Solution of Boundary Value Problems With Exact Satisfaction of Arbitrary Boundary Conditions

(2009) K.S. McFall et al.   IEEE TRANSACTIONS ON NEURAL NETWORKS

Solving differential equations with constructed neural networks

(2009) Ioannis G. Tsoulos et al.   NEUROCOMPUTING

Numerical solution of the nonlinear Schrodinger equation by feedforward neural networks

(2007) Yazdan Shirvany et al.   Communications in Nonlinear Science and Numerical Simulation