An Oil-water Layer Recognition System Based on Composition Intelligence Computation

DOI

10.2991/iske.2007.2How to use a DOI?

Keywords

attribute reduction; neural network; genetic algorithm; oil-water layer recognition

Abstract

In this paper, a composition intelligence computing method is suggested for an oil-water layer recognition system. The redundant condition attributes are reduced based on rough set attribute simplification algorithm so that an oil-water layer neural network recognition system can be simplified in order to improve network training speed. A local minimum problem of optimization computation of neural network is improved by a composition GA BP learning algorithm. Simulation result shows that the effect in oil-water layer recognition is improved by the composition intelligence computing method proposed here

Copyright

© 2007, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Huanglin Zeng
AU  - Juan Li
PY  - 2007/10
DA  - 2007/10
TI  - An Oil-water Layer Recognition System Based on Composition Intelligence Computation
BT  - Proceedings of the 2007 International Conference on Intelligent Systems and Knowledge Engineering (ISKE 2007)
PB  - Atlantis Press
SP  - 6
EP  - 9
SN  - 1951-6851
UR  - https://doi.org/10.2991/iske.2007.2
DO  - 10.2991/iske.2007.2
ID  - Zeng2007/10
ER  -