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Proceedings Paper

An improved membrane algorithm for solving time-consuming water quality retrieval
Author(s): Liang Zhong; Wenfei Luo
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Paper Abstract

Retrieving the parameters in water quality with multispectral data using neural network is increasingly popular, however, the training process with large amount samples and calculation with large-volume data are a time-consuming work. Many emergency pollution events need quick responses for practical use. In this paper, an improved membrane computing strategy is presented. This strategy is a hybrid one combining the framework and evolution rules of P systems with active membranes and neural networks, and it involves a dynamic structure including membrane fusion and division, which helpful to enhance the information communication and beneficial to reduce the computation. Then, a parallel implementation with the training result is discussed. Experiments with Landsat datasets to obtain suspended sediment are carried out to demonstrate the practical capabilities of this introduced strategy.

Paper Details

Date Published: 5 December 2011
PDF: 7 pages
Proc. SPIE 8005, MIPPR 2011: Parallel Processing of Images and Optimization and Medical Imaging Processing, 800509 (5 December 2011); doi: 10.1117/12.901923
Show Author Affiliations
Liang Zhong, Guangdong Technical College of Water Resources and Electric Engineering (China)
Wenfei Luo, South China Normal Univ. (China)

Published in SPIE Proceedings Vol. 8005:
MIPPR 2011: Parallel Processing of Images and Optimization and Medical Imaging Processing
Faxiong Zhang; Faxiong Zhang, Editor(s)

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