A parallel GA-BP neural network algorithm for solving inverse heat conduction problem

Author

Chen Yan ; Ma Li ; Guo Qingping

Author_Institution

Guilin Coll. of Aerosp. Technol., Guilin, China

Volume

9

fYear

2011

fDate

12-14 Aug. 2011

Firstpage

4622

Lastpage

4625

Abstract

Inverse heat conduction problem (IHCP) is a nonlinear, ill-posed problem of huge calculation, which is difficult to be solved properly. This paper proposes a parallel GA-BP algorithm on cluster for solving IHCP, which combine the ability of nonlinear mappings of forward back propagation (BP) neural network and the capacity of global optimization of genetic algorithm (GA). The processes of optimization algorithm and data parallelism are introduced mainly in this paper. The experimental results show that the method can achieve high speedup and improve computational efficiency.

Keywords

backpropagation; genetic algorithms; heat conduction; inverse problems; neural nets; physics computing; back propagation neural network; data parallelism; genetic algorithm; inverse heat conduction problem; nonlinear mappings; optimization algorithm; parallel GA-BP neural network algorithm; Algorithm design and analysis; Biological cells; Clustering algorithms; Computers; Genetic algorithms; Heuristic algorithms; Training; BP neural network; GA; IHCP; Parallel; speedup;

fLanguage

English

Publisher

ieee

Conference_Titel

Electronic and Mechanical Engineering and Information Technology (EMEIT), 2011 International Conference on

Conference_Location

Harbin, Heilongjiang

Print_ISBN

978-1-61284-087-1

Type

conf

DOI

10.1109/EMEIT.2011.6024005

Filename

6024005