Integration of results from recognition algorithms and its realization at the uranium production process

Author

Gritsenko, P. ; Iskakov, S. ; Muhamediyev, R. ; Yakinin, K.

Author_Institution

CSSE&T Dept., IITU, Almaty, Kazakhstan

fYear

2014

fDate

15-17 Oct. 2014

Firstpage

1

Lastpage

4

Abstract

Taught systems such as artificial neural network (ANN) can be used for data interpretation of electric logging. Using only the ANN algorithm gives the result of coincidence between interpretable data and experimental results in certain samplings from 66% to 73%. But using additional algorithms of recognition and integrating the results of recognition could enhance quality of recognition by 1-3%. The problem of integration of classification algorithms results was formulated and realization as pseudocode was shown.

Keywords

neural nets; pattern classification; production engineering computing; ANN algorithm; artificial neural network; classification algorithms; data interpretation; electric logging; pseudocode; taught systems; uranium production process; Algorithm design and analysis; Artificial neural networks; Biological neural networks; Classification algorithms; Estimation; Rocks; Support vector machines; Lithology; ensemble of algorithms; machine learning; pseudocode; uranium deposit;

fLanguage

English

Publisher

ieee

Conference_Titel

Application of Information and Communication Technologies (AICT), 2014 IEEE 8th International Conference on

Conference_Location

Astana

Print_ISBN

978-1-4799-4120-9

Type

conf

DOI

10.1109/ICAICT.2014.7035940

Filename

7035940