Quantitative retrieval of suspended solid concentration in Lake Taihu based on BP neural net
A two-layer BP neural net model is constructed with four input nodes of TM1, 2, 3, 4 band reflectances, and one output node of suspended solid concentration (SSC) to retrieve SSC of Lake Taihu. The results demonstrated that BP neural net is very fit to quantitatively retrieve water quality of case I...
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2006
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sg-smu-ink.sis_research-76862022-01-13T05:30:03Z Quantitative retrieval of suspended solid concentration in Lake Taihu based on BP neural net LYU, Heng LI, Xingguo CAO, Kai A two-layer BP neural net model is constructed with four input nodes of TM1, 2, 3, 4 band reflectances, and one output node of suspended solid concentration (SSC) to retrieve SSC of Lake Taihu. The results demonstrated that BP neural net is very fit to quantitatively retrieve water quality of case II water with complex optic characteristic, and has much higher accuracy than the common linear model. A test was made and the results suggest that 13 had relative error (RE)RE of less than 30%, accounting for 81.25% of the total samples. 2006-08-05T07:00:00Z text https://ink.library.smu.edu.sg/sis_research/6683 Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Databases and Information Systems OS and Networks |
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Databases and Information Systems OS and Networks LYU, Heng LI, Xingguo CAO, Kai Quantitative retrieval of suspended solid concentration in Lake Taihu based on BP neural net |
| description |
A two-layer BP neural net model is constructed with four input nodes of TM1, 2, 3, 4 band reflectances, and one output node of suspended solid concentration (SSC) to retrieve SSC of Lake Taihu. The results demonstrated that BP neural net is very fit to quantitatively retrieve water quality of case II water with complex optic characteristic, and has much higher accuracy than the common linear model. A test was made and the results suggest that 13 had relative error (RE)RE of less than 30%, accounting for 81.25% of the total samples. |
| format |
text |
| author |
LYU, Heng LI, Xingguo CAO, Kai |
| author_facet |
LYU, Heng LI, Xingguo CAO, Kai |
| author_sort |
LYU, Heng |
| title |
Quantitative retrieval of suspended solid concentration in Lake Taihu based on BP neural net |
| title_short |
Quantitative retrieval of suspended solid concentration in Lake Taihu based on BP neural net |
| title_full |
Quantitative retrieval of suspended solid concentration in Lake Taihu based on BP neural net |
| title_fullStr |
Quantitative retrieval of suspended solid concentration in Lake Taihu based on BP neural net |
| title_full_unstemmed |
Quantitative retrieval of suspended solid concentration in Lake Taihu based on BP neural net |
| title_sort |
quantitative retrieval of suspended solid concentration in lake taihu based on bp neural net |
| publisher |
Institutional Knowledge at Singapore Management University |
| publishDate |
2006 |
| url |
https://ink.library.smu.edu.sg/sis_research/6683 |
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