A new application of the cost function-based rearrangement of genes (proposed by Liu
(2008)[1]) is presented in this paper through the genetic algorithm-based solution of the …

An artificial neural network based solution of the inverse heat conduction problem of
simultaneous identification of the temperature-dependent volumetric heat capacity and …

In this paper, the conjugate gradient method coupled with adjoint problem is used in order to
solve the inverse heat conduction problem and estimation of the time-dependent heat flux …

This article describes a methodology for using neural networks in an inverse heat
conduction problem. Three neural network (NN) models are used to determine the initial …

This paper proposes a hybrid approach, wherein Markov Chain Monte Carlo (MCMC)
simulations are used in a Bayesian framework, in conjunction with artificial neural networks …

Using neural networks to obtain initial estimates for the solution of inverse heat transfer problems
Page 359 358 Inverse Problems, Design and Optimization USING NEURAL NETWORKS TO …

In this paper, the conjugate gradient method, coupled with the adjoint problem, is used to
solve the inverse heat conduction problem and to estimate the time-dependent heat flux …

A new evaluation method based on a genetic algorithm is applied for simultaneous
determination of the temperature-dependent thermal conductivity and volumetric heat …

We present a solution for an inverse heat transfer problem involving internal heat generation
using artificial neural networks. The problem involves a heat conduction problem with …

In this paper, the conjugate gradient method, coupled with the adjoint problem, is used in
order to solve the inverse heat conduction problem and estimation of the time-dependent …