5 December 2011 An improved membrane algorithm for solving time-consuming water quality retrieval
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Proceedings Volume 8005, MIPPR 2011: Parallel Processing of Images and Optimization and Medical Imaging Processing; 800509 (2011) https://doi.org/10.1117/12.901923
Event: Seventh International Symposium on Multispectral Image Processing and Pattern Recognition (MIPPR2011), 2011, Guilin, China
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.
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Liang Zhong, Wenfei Luo, "An improved membrane algorithm for solving time-consuming water quality retrieval", Proc. SPIE 8005, MIPPR 2011: Parallel Processing of Images and Optimization and Medical Imaging Processing, 800509 (5 December 2011); doi: 10.1117/12.901923; https://doi.org/10.1117/12.901923
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