Research on Application of BP Networks in the Naval Minesweeping Effectiveness Estimating

Author

Meng Jing ; Li Qingmin ; Li Hua

Author_Institution

Dept. of Weaponry Eng., Naval Univ. of Eng., Wuhan, China

Volume

1

fYear

2009

fDate

28-30 Oct. 2009

Firstpage

447

Lastpage

450

Abstract

The application of back propagation(BP) neural networks in the Naval Minesweeping Effectiveness Estimating (NMEE) was investigated by introducing the theory of BP artificial neural network (BPANN) and establishing a learning algorithm of forecasting for minesweeping effectiveness under a certain battle-field situation. A three-layer BP network was designed and a computer program was written based on the advanced BP algorithm using Matlab 6.0 language. The results were satisfying within an acceptable error margin after some sample data were normalized and learned by BPANN.

Keywords

backpropagation; learning (artificial intelligence); mathematics computing; naval engineering computing; neural nets; weapons; Matlab 6.0 language; back propagation neural networks; battle field situation; forecasting; learning algorithm; naval minesweeping effectiveness estimation; Application software; Artificial neural networks; Biological neural networks; Brain modeling; Computer networks; Computer science; Information analysis; Mathematical model; Multi-layer neural network; Weapons; BP Algorithm; effectiveness; estimating; minesweeping; neural network;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer Science and Engineering, 2009. WCSE '09. Second International Workshop on

Conference_Location

Qingdao

Print_ISBN

978-0-7695-3881-5

Type

conf

DOI

10.1109/WCSE.2009.707

Filename

5403239