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Fuzzy Integral Based Information Fusion for Water Quality Monitoring Using Remote Sensing Data
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International Journal of Communications, Network and System Sciences·Volume 03 (2010)·Pages 737–744·Published 30 September 2010·DOI10.4236/ijcns.2010.39098
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Abstract
To improve the monitoring precision of lake chlorophyll a (Chl-a), this paper presents a fusion method based on Choquet Fuzzy Integral (CFI) to estimate the Chl-a concentration. A group of BPNN models are designed. The output of multiple BPNN model is fused by the CFI. Meanwhile, to resolve the over-fitting problem caused by a small number of training sets, we design an algorithm that fully considers neighbor sampling information. A classification experiment of the Chl-a concentration of the Taihu Lake is conducted. The result shows that, the proposed approach is superior to the classification using a single neural network classifier, and the CFI fusion method has higher identification accuracy.
KeywordsWater Quality MonitoringRemote SensingNeural NetworksFuzzy IntegralInformation Fusion
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