Fuzzy Integral Based Information Fusion for Water Quality Monitoring Using Remote Sensing Data
Huibin Wang, Tanghuai Fan, Aiye Shi, Fengchen Huang, Huimin Wang
DOI: 10.4236/ijcns.2010.39098   PDF    HTML     4,525 Downloads   8,563 Views   Citations

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.

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H. Wang, T. Fan, A. Shi, F. Huang and H. Wang, "Fuzzy Integral Based Information Fusion for Water Quality Monitoring Using Remote Sensing Data," International Journal of Communications, Network and System Sciences, Vol. 3 No. 9, 2010, pp. 737-744. doi: 10.4236/ijcns.2010.39098.

Conflicts of Interest

The authors declare no conflicts of interest.

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