Application of genetic neural network on geological environment assessment

Author

Yang, Qiang ; Wen, Pengquan ; Long, Xiaojun ; Li, Xiaoqiong ; Liu, Min

Author_Institution

Coll. of Nucl. Technol. & Autom. Eng. Inst., ChengDu Univ. of Technol., Chengdu, China

fYear

2011

fDate

16-18 Sept. 2011

Firstpage

1451

Lastpage

1454

Abstract

This paper introduced a new way which utilizes genetic algorithm to optimize neural network weights. And we have worked out the algorithm on ARCGIS and MATLAB platform. Meanwhile, a comprehensive evaluation of environment carrying capacity on Jiulong county has been carried out. The findings and results show that this method can provide a new way to evaluate geological environment, because it can effectively avoid the complicated parameter estimation process and adapt to the assessment of an unknown system in a complex environment.

Keywords

backpropagation; environmental science computing; genetic algorithms; geographic information systems; geology; neural nets; parameter estimation; ARCGIS platform; BP neural network; China; Jiulong county; MATLAB platform; environment carrying capacity; genetic algorithm; genetic neural network; geological environment assessment; geological environment evaluation; neural network weight optimization; parameter estimation; Artificial neural networks; Educational institutions; Genetic algorithms; Genetics; Geology; MATLAB; Sun; ARCGIS; BP neural network; MATLAB; genetic algorithm; geological environment assessment;

fLanguage

English

Publisher

ieee

Conference_Titel

Electrical and Control Engineering (ICECE), 2011 International Conference on

Conference_Location

Yichang

Print_ISBN

978-1-4244-8162-0

Type

conf

DOI

10.1109/ICECENG.2011.6058328

Filename

6058328