Research on the Method of Warfare Simulation Data Analysis Based on BP Neural Network and RoughSet

Jun Heng; Yun Fei Tian; Peng Yan

doi:10.4028/www.scientific.net/AMR.765-767.498

Paper Titles

Simulating Polydisperse Ellipsoid Particles System
p.482

Clustering Algorithm Based on Improved Particle Swarm Optimization
p.486

An Improved BP Algorithm and its Application
p.489

Particle Matching Algorithm for 3D-PIV Based on Delaunay Triangulation
p.493

Research on the Method of Warfare Simulation Data Analysis Based on BP Neural Network and RoughSet
p.498

Delay-Dependent Stochastic Stability Analysis of Singular Hybrid System
p.504

Multi-Objective Coverage Alogrithm for WSN Based on Particle Swarm Optimization
p.508

Numerical Simulation of Turbulent Driven Secondary Flow in a 90° Bend Pipe
p.514

Delay Dependent H∞ Stochastic Stability Analysis for Stochastic Nonlinear Delay Hybrid Singular System
p.520

HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 765-767Research on the Method of Warfare Simulation Data...

Research on the Method of Warfare Simulation Data Analysis Based on BP Neural Network and RoughSet

Abstract:

Preliminary exploration on simulation data mining with BP network and rough set method is made in the paper. Data mining method based on rough set theory and BP neural network is put up. Firstly, we reduce the redundant attributes in the decision-making table with rough set method, and then the noise is filtered by BP neural network. Finally, rule set is generated by rough set from the reduction decision table. This method not only avoids the complexity of the rules extracted from training the neural network, but also improves the classification accuracy effectively. At last, the mining data by the experimental data of the troops marching warfare simulation system and the result with the actual reference value is obtained.

You might also be interested in these eBooks

View Preview

Info:

Periodical:

Advanced Materials Research (Volumes 765-767)

Pages:

498-503

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.765-767.498

Citation:

Cite this paper

Online since:

September 2013

Authors:

Jun Heng, Yun Fei Tian, Peng Yan

Keywords:

BP Neural Network (BPNN), Rough Set (RS), Rules, Warfare Simulation

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

References

[1] Ortiz Rivera, William, Pacheco Londono, Leonardo C, Hernondez Rivera, Samuel P. Remote continuous wave and pulsed laser raman detection of chemical agents simulants. Sensing and Imaging, 2010(131-145).

DOI: 10.1007/s11220-010-0055-9

Google Scholar

[2] Ramaseshan, Ramakrishnan, Ramakrishna, Seeram. Zinc titanate nanofibers for the detoxification of chemical simulants, Journal of the American Ceramic Society, 2007(1836-1842).

DOI: 10.1111/j.1551-2916.2007.01633.x

Google Scholar

[3] Cui, Xiaohui, Potok, Thomas E. A particle swarm social model for multi-agent based insurgency simulation. Proceedings of SERA 2007: Fifth ACIS International Conference on Software Engineering Research, Management, and Applications, 2007(177-183).

DOI: 10.1109/sera.2007.21

Google Scholar

[4] Wang, Shuo, Xu, Kaiying, Zhang, Yong. Search engine optimization based on algorithm of BP neural nnetworks. Proceeding of 2011 7th International Conference on Computational Intelligence and Security, 2011(390-394).

DOI: 10.1109/cis.2011.93

Google Scholar

[5] Ostak, Alexander. Towards the theory of M-approximate systems: Fundamentals and examples. Fuzzy Sets and Systems, 2010(2440-2461).

Google Scholar

[6] Zhao, Jianou , Mao, JianMin; Shi, YanNi. Highway tunnel traffic accidents prediction model based on BP neural network. Beijing Institute of Technology (English Edition), 2010(95-99).

Google Scholar

[7] Sakthivel, N. R, Sugumaran, V, Nair, Binoy B. Automatic rule learning using roughset for fuzzy classifier in fault categorization of mono-block centrifugal pump. Applied Soft Computing Journal, 2012(196-203).

DOI: 10.1016/j.asoc.2011.08.053

Google Scholar