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Numerical Heat Transfer, Part A: Applications
An International Journal of Computation and Methodology
Volume 59, 2011 - Issue 12
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Original Articles

A Modified Sequential Particle Swarm Optimization Algorithm with Future Time Data for Solving Transient Inverse Heat Conduction Problems

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Pages 911-933 | Received 24 Nov 2010, Accepted 09 Apr 2011, Published online: 08 Jun 2011
 

Abstract

The particle swarm optimization (PSO) method is modified and employed to solve the inverse heat conduction problem. Since the main drawback of PSO in solving inverse problems is its slow convergence, most of the modifications in this research are aimed at overcoming this downside. A sequential implementation and a multi-criteria optimization formulation are designed to accelerate the convergence in transient multi-sensor applications. The concept of future time steps is used to make the PSO-based inverse analyzer more stable in dealing with measurement noise. All these modifications are found to be effective in improving the behavior of the algorithm.

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