The aim of this paper is to design feed forward neural network for solving second‐order
singular boundary value problems in ordinary differential equations. The neural networks …

This work does not use the classical methods (simplex method, Branch and Bound
techniques) which were normally used for solving Linear programming models. The …

In this study we investigate neural network solutions to nonlinear differential equations of
Ricatti-type. We employ a feed-forward Multilayer Perceptron Neural Network (MLPNN), but …

The aim of this paper is to presents a parallel processor technique for solving eigenvalue
problem for ordinary differential equations using artificial neural networks. The proposed …

The paper examined some alternative numerical integration methods and their errors in the
circuit transient analysis packages. We compared in term of accuracy and stability and …

The aim of this paper is to train feed forward neural network for solving some class of
boundary value problems for ordinary differential equations. Using backpropagation training …

The aim of this paper is to design collocation neural network to solve second order nonlinear
boundary value problems in singular ordinary differential equations. The proposed network …

Aulas experimentais são indispensáveis para o adequado aprendizado de conteúdos de
Física. Nos últimos anos, surgiram diversos softwares de simulação de experimentos de …

Time series function is defined as a sequence of vector or scalar values which depend on
time. NN, have been widely used as time series forecasting like weather forecast and load …

Esta revisão bibliográfica tem por objetivo fundamental fazer uma pequena apresentação
da informação disponível nos periódicos de Ensino de Ciências e matemática sobre os …