Forestry Fire Spatial Diffusion Model Based on Integration of Multi-Agent Algorithm with Cellular Automata

Authors

Zhao Di, Institute of Disaster Prevention Science and Safety Technology, Central South University, Changsha 410075, China;
Zhisheng Xu, Institute of Disaster Prevention Science and Safety Technology, Central South University, Changsha 410075, China;

Abstract

Abstract: In view of the existing ultrasonic detection signal attenuation, directional difference, complex propagation paths, and characteristics of the components of complex, a kind of intelligent concrete defect nondestructive detection algorithm based on multi resolution singular entropy was put forward. By using the wavelet algorithm, the ultrasonic signal was decomposed into high, low frequency components of multi scales for each component, then each component was decomposed by singular spectrum analysis, at the same time using the information entropy theory, the calculation of singular entropy as the characteristic defect detection value, using the GA-SVM algorithm was used to train the singular entropy, so as to achieve the purpose of identification of defects in concrete. The simulation results show that the proposed method can effectively improve the accuracy of the identification of the defects, and it can provide a new effective way to identify the defects of the concrete.

Recommended Citation

Di, Zhao and Xu, Zhisheng (2020) "Forestry Fire Spatial Diffusion Model Based on Integration of Multi-Agent Algorithm with Cellular Automata," Journal of System Simulation: Vol. 29: Iss. 4, Article 8.
DOI: 10.16182/j.issn1004731x.joss.201704008
Available at: https://dc-china-simulation.researchcommons.org/journal/vol29/iss4/8

First Page

761

Revised Date

2016-05-18

DOI Link

https://doi.org/10.16182/j.issn1004731x.joss.201704008

Last Page

766

CLC

TP273

Recommended Citation

Zhao Di, Xu Zhisheng. Forestry Fire Spatial Diffusion Model Based on Integration of Multi-Agent Algorithm with Cellular Automata[J]. Journal of System Simulation, 2017, 29(4): 761-766.

DOI

10.16182/j.issn1004731x.joss.201704008