Journal
MARINE POLLUTION BULLETIN
Volume 119, Issue 1, Pages 307-319Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.marpolbul.2017.04.022
Keywords
Eutrophication assessment; Easily measured parameters; CDOM; Fluorescence; TRIX; Support vector machine
Funding
- Natural Science Foundation of China [41376106]
- National Key Research and Development Program [2016YFC1402101]
- Research Program from National Marine Hazard Mitigation Service [2014AA060]
Ask authors/readers for more resources
The development of techniques for real-time monitoring of the eutrophication status of coastal waters is of great importance for realizing potential cost savings in coastal monitoring programs and providing timely advice for marine health management. In this study, a GS optimized SVM was proposed to model relationships between 6 easily measured parameters (DO, Chl-a, C1, C2, C3 and C4) and the TRIX index for rapidly assessing marine eutrophication states of coastal waters. The good predictive performance of the developed method was indicated by the R-2 between the measured and predicted values (0.92 for the training dataset and 0.91 for the validation dataset) at a 95% confidence level. The classification accuracy of the eutrophication status was 86.5% for the training dataset and 85.6% for the validation dataset. The results indicated that it is feasible to develop an SVM technique for timely evaluation of the eutrophication status by easily measured parameters.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available